Veröffentlichungen von Prof. Dr.-Ing. Gisela Lanza

In the manufacturing industry, target-oriented and efficient use of resources is gaining importance, alongside economic optimization. The economic and organizational optimization of manufacturing systems according to the lean principles is only partly compatible with the goals of resource-efficient manufacturing. Therefore, an approach is sought to improve individual analyses of manufacturing systems. This paper proposes an approach for the multi-objective optimization of lean and resource-efficient manufacturing systems. To predict the dynamic effects of several configurations of manufacturing systems, material, energy, and information flows of a discrete event simulation are coupled with an assessment model, based on objectives of lean and resource-efficient manufacturing. Using design of experiments, Gaussian process meta-models are computed for the behavior of the simulation model. These meta-models allow the approximation of the system behavior to be computed in a short period of time and enable extensive multi-objective optimization and more adequate decision-making support systems. The proposed approach is tested in the metalworking industry.

Among the current challenges to the global automotive industry are changes in global markets leading to product variety, regulation leading to pressure for new technologies in body and powertrain, and competition by new players such as huge information and communication technology companies. Automotive original equipment manufacturers (OEMs) deal with these issues in different ways. This paper uses the scenario technique to illustrate possible answers to the question, how future value chains of automotive industry will look like. In almost all cases, Information and communication technology (ICT) plays a major role in future strategies to cope with the aforementioned challenges. On the one hand, ICT can boost the way to more efficient production of variants by utilizing smart manufacturing approaches, on the other hand ICT enables new features such as autonomous driving.

This optimisation approach focuses on the shop floor of a manufacturing company. It aims for an integrated lean and green assessment of a manufacturing system and the identification of a cost optimized combination of lean and green strategies with regard to green targets. For green assessment material and energy inputs as well as resulting CO2 emissions are taken into account. Lean assessment focuses on costs and throughput time. Potential lean and green strategies identified during top down analysis are integrated into a discrete event simulation model. This model is connected with optimisation heuristics which improve combined lean and green strategy deployment to the manufacturing system.

Die Klebetechnik gewinnt als zukunftsträchtige, variabel einsetzbare Fügetechnik immer mehr an Bedeutung. Um Ausschuss zu vermeiden und Prozesse steuern zu können, müssen zerstörungsfreie Qualitätssicherungsmaßnahmen in die Prozessketten integriert werden. Ultraschallbasierte Messkonzepte bieten hierfür eine mögliche Lösung zur Detektion von qualitätskritischen Lufteinschlüssen bei der Applikation von Kleberaupen.

Bei unreifen Produktionstechnologien, wie der Batterieproduktion für elektromobile Anwendungen, ist eine geeignete Integration von Mess- und Prüftechnik in die Prozesskette von großer Relevanz. Der Fachartikel stellt einen Ansatz zur Planung der Prüfmittelallokation in einer Prozesskette vor. Die Methodik beruht auf der Kombination von Simulations- und Optimierungsverfahren.

Prozessfähigkeitsuntersuchungen vergleichen die Verteilung eines Fertigungsprozesses mit den definierten Toleranzen eines Qualitätsmerkmals. Allerdings kann die Messunsicherheit die beobachtete Qualität des Fertigungsprozesses dabei erheblich beeinflussen. Um die Untersuchung von Prozessfähigkeiten in der diskreten Fertigung zu verbessern, wird die „Entfaltung“ als allgemeine Methode zur mathematischen Korrektur von systematischen und zufälligen Messabweichungen vorgeschlagen.

In-process measurements by machine tools offer high product quality, lower manufacturing costs, high productivity and a real-life assessment of product quality. Measurement errors of machine tools are influenced by complex environmental factors on the shop floor (e.g. temperature). The project ‘‘Traceable In-Process Dimensional Measurement’’ (TIM) aims for the ability to measure fabricated parts accurately in-process under the influence of the previously named factors. The development of a mobile climate simulation chamber is one of the work packages in this project and has the objective to simulate shop floor conditions to which a machine tool is exposed in its daily use. Based on the analysis of the variety of influencing factors, different concepts for the design of the mobile simulation chamber have been elaborated and the final concept was chosen. The validation of the final concept was supported by a computational fluid dynamics simulation and a modified temperature sensor distribution that is fit for the described purpose with regard to the mobility and thermal stability of the system.

In high-tech production, companies often deal with the manufacturing of assemblies with quality requirements close to the technological limits. Selective and adaptive production systems are means to cope with this challenge. In this context new measurement technologies and IT-systems offer the opportunity to generate and use real-time quality data along the process chain and to control the production system adaptively. In this article, a holistic matching approach to optimize the performance of selective and adaptive assembly systems is presented and its industrial application within an automotive electric drive assembly is demonstrated.

Neben den klassischen Zielgrößen Kosten, Zeit und Qualität sind Unternehmen zunehmend mit Forderungen nach Ressourceneffizienz (Energie, Material) und Verringerung von CO2-Emissionen konfrontiert. In aller Regel stellt die Wirtschaftlichkeit jedoch weiterhin das entscheidende Kriterium bei der Einführung „grüner“ Maßnahmen dar. Der Fachbeitrag beschreibt eine Methodik zur Planung und Bewertung von Maßnahmen zur wirtschaftlichen Gestaltung von Produktionssystemen unter Berücksichtigung „grüner“ Grenzwerte.

Today an efficient warehouse and inventory management of spare parts for production machinery is essential for service organizations. Optimal strategies in procurement, stocking and supply play an important role for serviceability in spare parts management. In this context, individual item criticality should be considered, which describes how crucial a spare part is. This paper presents a three-dimensional classification approach for spare parts regarding a cross-plant central warehouse strategy of a service network. The approach uses two dimensions to estimate value and predictability of spare parts with aid of an ABC and XYZ analysis. The third dimension VED analyses a multi-criteria criticality classification and six feasible criteria are identified to describe item criticality. The methodology of the analysis is based on a decision tree, which represents the defined criteria by nodes. In addition, the analytic hierarchy process is used to solve the multi-criteria decision problems at the different nodes of the decision tree. The approach is developed in a Research project and evaluation of spare parts is performed based on real inventory and transaction data in cooperation with an industrial company. As a result 15,000 out of 50,000 items could be classified as suitable for central warehousing.

The automotive industry can be described as a backbone in many developed countries such as Japan, Korea, USA, and Germany, while being an enabler for economic prosperity in developing countries like China, Brazil, Eastern Europe, and Russia at the same time. However, the dynamics and uncertainty are increasing heavily by market changes, regulations, customer behavior, and new product technologies. Manufacturing research has to find answers to increase quality of products, flexibility of plants, and supply chain networks, to manage complexity in technologies and variants and overall to stay competitive even in high wage countries. In this paper, major technological challenges are discussed and the current state of manufacturing technology and research is presented. Moreover, for each technological and organizational area, future industrial, and research challenges are highlighted.

There is a decent number of possible heuristic methods to solve an actual problem in production planning and control. Usually, each solving method leads to a different alternative. In dynamic production environments, decision makers often have to decide between uncertainty and risk. Making multi-criteria decisions under risk is a well-known problem. In this paper, we will consider rescheduling as an example for decision-making in a dynamic production environment. It is used to present an intelligent manufacturing approach for multi-criteria decisions under risk that combines a method for decisionmaking under risk and a multi-attribute decision-making method. Moreover, for frequently appearing problems, such as rescheduling, a procedure to evaluate the used solving methods is presented. We use this information to achieve a sustainable improvement for the solving procedure of future manufacturing problems.

By designing global manufacturing networks still purely cost-based decisions are made, in which objectives such as delivery time, quality, flexibility, closeness to customer and coordination effort are neglected. The design and decision-making process becomes more complex, the more influencing factors of the business environment are considered. Due to the dynamic and uncertainty of these factors a decision support is required which includes all relationships in the network and its environment. This paper presents a dynamic multi-objective optimization model for global manufacturing networks, which evaluates the impact of changes of influencing factors and optimizes the global design of the manufacturing network.

Vorgestellt wird eine neuartige Metrik zum Vergleich von Produktionsprozessen bezüglich ihrer Ähnlichkeit und daraus abgeleitet hinsichtlich möglicher Synergie- und Integrationspotentiale. Nach einer Übersicht über den Stand der Technik veranschaulicht ein Beispiel aus der Automobilindustrie (Brennstoffzellen- und Li-Ionen-Batteriezellenfertigung) die Anwendbarkeit der Metrik.

"Rescheduling" ist ein notwendiges Instrument der adaptiven Produktionsplanung und -steuerung. Der Fachartikel beschreibt eine Methode zur Bewertung und Auswahl verschiedener als Reaktion auf eine Störung erstellter Produktionspläne, unter Berücksichtigung aller durch das Rescheduling verursachter Aufwände. Hierfür wird ein Ansatz zur systematischen Identifizierung vorgestellt.

Mikrozahnräder sind wichtige Bauteile in vielfältigen innovativen Anwendungen. Die Computertomografie (CT) bietet aufgrund ihrer hohen Informationsdichte großes Potential für deren Qualitätssicherung. Der Fachartikel beschreibt eine Methode zur Genauigkeitssteigerung von CT-Messungen der Mikrozahnräder. Hierfür wird ein Ansatz vorgestellt, bei dem die CT-Messdaten mit hochgenauen taktilen Messdaten fusioniert werden.

Die zunehmend nachgefragten und oft aus Sicht der Hersteller schwer kalkulierbaren Bestandteile der TCO (Total Cost of Ownership)-Verträge bestehen aus verschiedenen Kostenblöcken, wobei die Instandhaltungs- und Energiekosten dominieren. Diese Kosten sind wesentlich vom individuellen Anwendungsfall abhängig. Um die Auswirkungen der verschiedenen Nutzungsprofile im TCO-Vertrag ausreichend berücksichtigen zu können, entwickelt das wbk zusammen mit Industriepartnern einen neuen transparenten und anwendbaren Standard, der auf Referenzklassen beruht.

Bei der Elektrifizierung des Antriebsstrangs steht die kosteneffiziente Batterieproduktion im Fokus. Die ungewisse Marktentwicklung, die große Produktvielfalt sowie die unreife Li-Ionen-Technologie stellen besondere Herausforderungen der Elektromobilität dar. Zudem hängt die Lebensdauer der Batteriesysteme von der Fertigungsqualität ab. Daher ist ein qualitätsorientierter Planungsansatz für eine wandlungsfähige Batteriemontage erforderlich.

Light-weight aluminum space frame structures are frequently used for small-volume products, suchas sports cars. The assembly of these products has so far been mainly manual and requires the use ofcomplex and expensive fixtures. To increase the profitability the research conducted at wbk Institute ofProduction Science is aiming to achieve an automated, fixtureless assembly of such structures by the useof industrial robots. To achieve the required accuracies regarding the alignment of the joining partners, anew approach based on component-inherent markings has been developed. Different tests have alreadybeen conducted in order to validate the approach. The test results demonstrate that the approach issuitable for the spatial alignment of components.This article describes the theoretical foundations of the required measurement approach as well as theexperimental results.

Unter dem Begriff „Life Cycle Performance“ werden die Bewertung, Optimierung und Gestaltung von zuverlässigen und effizienten Systemen im Maschinen- und Anlagenbau über den gesamten Lebenszyklus verstanden [1]. Mit modernen Methoden der Informations- und Kommunikationstechnik sind wesentliche Erleichterungen für Maschinenbetreiber sowohl im technischen als auch organisatorischen Umfeld erreichbar. Der Fachbeitrag geht dabei auf die strategischen sowie technischen Herausforderungen für den intelligenten Betrieb ein und stellt die bereits entwickelten Lösungsansätze im Umfeld des Trends "Industrie 4.0" vor.

Sustainable individual mobility can only be achieved by reducing the energy consumption and consequently the CO2 emissions. Solutions therefore can be found in the reduction of the motor cars moving mass. This is forced by the trend towards electric vehicles, the increasing safety and new comfort oriented functions. To achieve the aim of mass reduction, lightweight material design plays an important role. To exploit the entire potential of lightweight design, fiber-reinforced plastics (FRP) are also being considered by the automotive industry in addition to the traditional lightweight materials such as aluminium and magnesium alloys. However, due to the current low automation rate and high production costs especially carbon-fiber-reinforced plastics (CFRP) are not widely used. Especially the automation of the draping-process - the forming operation of semi-finished textiles - and the aligned quality assurance has to be developed. Imperfections, which occur in this process step, can influence the performance of the part in a significant way. At the moment, these defects are only detected at the end of the entire production, which leads to high costs caused by scrap. This paper provides an approach how inline metrology can be integrated into the production process. Hereby, the focus is set on the different measurement systems which are used for the detection of several kinds of defects as well as on the measurement strategy which is highly responsible for a time efficient measurement.

Die Auswahl der Inline-Messtechnik für das „Preforming“ von textilen Halbzeugen in der CFK (kohlenstofffaserverstärkter Kunststoff)-Fertigung ist an vielfältige Anforderungen geknüpft. Um die Bewertung der Messtechnik und somit den Auswahlprozess zu vereinfachen, wurden Prüfkörper entwickelt, die typische Imperfektionen und Preform-Geometrien abbilden.

The automotive industry faces major challenges due to volatile markets and expenses for new technologies. The dynamics of markets and future technological variety demand flexibility. A sustainable transformation strategy is indispensable for upcoming decades. The following paper presents an approach supporting both, tactical as well as strategic decision-making in volatile manufacturing environments. At first, operating costs and performance figures of manufacturing systems are calculated. In step two, a Markovian Decision Process is solved to find a cost minimal policy over planning horizons. The optimization of the manufacturing system is based on capacity adaptations and changes in process steps, suppliers, and locations.

Für produzierende Unternehmen an Hochlohnstandorten ist eine Kostenbetrachtung über Lebenszyklen entscheidend. Dies stellt sowohl Betreiber als auch Hersteller von Produktionsanlagen vor Herausforderungen. Am Institut für Produktionstechnik (wbk) des Karlsruher Instituts für Technologie (KIT) wurde der Forschungsschwerpunkt Life Cycle Performance (LCP) etabliert, welcher auf die Bewertung, Optimierung und Gestaltung von zuverlässigen und effizienten Systemen über den gesamten Lebenszyklus abzielt.

Green machining strategies can affect several aspects of a manufacturing system including part quality, which must remain sufficient to ensure the product's value. Improved part quality can also reduce life cycle environmental impacts through increased resource efficiency, which adds a further consideration. This paper quantifies the impact of these strategies on the achieved surface quality of turned titanium in the context of various resource costs including electrical energy, tool wear, and service costs. The results suggest that the final surface quality is most influenced by the finish cut(s) and feed rate. Part functionality is also an important consideration for resource efficiency.

Nowadays the number of product models constantly increases, due to a strong competition to innovate and the reduction of product life cycles, resulting in a more frequent occurrence of production ramp-ups. The production ramp-up combines the product development with the series production and has an impact on the market entry timing. In order to ensure an ideal ramp-up with new developed products being placed on the market as quickly as possible, there has to be an efficient use of existing resources, especially of human resources. Nevertheless, the planning of these resources turns out to be the most important challenge because it is directly related to a great uncertainty. The following article represents an approach that is being developed at the Institute of Production Science (wbk) of the Karlsruhe Institute of Technology (KIT) to optimize the forecast of the personnel requirements during ramp-up by taking into account the dynamic planning variables and organizational basic conditions. Therefore, a method will be developed that provides support to the responsible persons of the respective production ramp-up to calculate the necessary manpower for every single ramp-up phase and to realize the economic optimum. This method focuses on a simulation of the ramp-up process that allows an economically more efficient use of human resources.

Zur Leistungsbewertung von Produktionssystemen unter Berücksichtigung stochastischer Einflussgrößen - wie Nachfrageschwankungen oder Materialverknappung - eignen sich unter anderem analytische und simulationstechnische Ansätze. Der Fachbeitrag beschreibt drei hybride Modellierungsverfahren, mit deren Hilfe die Vorteile von analytischen Methoden und Simulation vereint werden und die zur Leistungsbewertung komplexer Produktionssysteme verwendet werden können. Entwickelt werden die beschriebenen hybriden Modellierungsverfahren seit Mai 2010 in einem interdisziplinären Projekt des Instituts für Fördertechnik und Logistiksysteme (IFL) sowie des Instituts für Produktionstechnik (wbk) des Karlsruher Instituts für Technologie (KIT). Die Forschungsarbeiten werden von der Deutschen Forschungsgemeinschaft (DFG) gefördert (DFG FU 273/8-1, LA 2351/6-1).

Today production planning has to deal with highly dynamic markets and increasing uncertainties. Moreover, it has to take into account possibilities of the surrounding production network. By combining a queueing theory model with a stochastic, dynamic optimization approach, a method to support decision making in production planning was developed. Hereby, a Markovian Decision Process is solved to find cost minimal policies as reactions to volatile market demands for minimizing costs due to capacity adaptations, changes in process steps, and locations. The method was applied at an automotive supplier to find suitable system configurations and investment decisions for an uncertain future.

Globally operating companies are set up in global value added networks. Their current environment is characterized by dynamism, complexity and uncertainty. Furthermore companies are constantly challenged to respond adequately to the rapid changes in environment. Therefore it is crucial to identify company-specific factors which require changes - so called drivers of change. This article presents a method to identify changing drivers of globally operating companies. In addition, the method enables to quantify the changing drivers and determines the effect relationships based on the application of a system dynamics approach. The presented method has been developed in the framework of the research project Design and optimization of changeable global value added networks (POWer.net) funded by Federal Ministry for Education and Research (BMBF) and managed by PTKA Karlsruhe.

Eine große Breite an Produkten am Markt anzubieten, während deren Lebenszyklusdauer abnimmt, stellt für Unternehmen eine Herausforderung dar. Insbesondere der frühe Markteintrittszeitpunkt und die daraus resultierende Reduktion von Lost Sales sind Wettbewerbsvorteile gegenüber der Konkurrenz. Schlüsselprozess ist die effiziente Ressourcenplanung des Produktionsanlaufs. Der Beitrag beschreibt die Entwicklung eines Modells zur Unterstützung der Prognose des Personalbedarfs im Produktionsanlauf.

Any decision a company takes concerning the global expansion of its value network has major economic implications and is highly complex. Many diverse aspects must be taken into consideration when such a decision is made to ensure that a robust network is configured which will allow the company to be economically successful in the future in spite of the volatile environment it is affected by. It is against this context that the LMP and the wbk jointly developed a decision support method for the configuration and evaluation of the global expansion of value networks. The successful implementation and application of the approach are shown on the basis of a practical case study.

In micrometer dimensions the uncertainty of measurement is essential for reliably determining part quality. However, calibrated standards are necessary to experimentally estimate the uncertainty of measurement. Due to the complex shape of micro gears (e.g. involute tooth flanks), which cannot be manufactured precisely enough to be represented in the standard, simple geometric elements are utilized. The presented novel micro gear standard uses cylinders to model the involute tooth flanks. The approach describes the estimation of the uncertainty of measurement for measurements of the profile, helix, pitch and tooth flank deviations. Furthermore, initial measurement results of a prototypical standard are provided.

Deutsche Produktionsunternehmen haben sich mit voranschreitender Globalisierung in globalen Wertschöpfungsnetzwerken aufgestellt. Bisher reagieren diese bei dynamischen Veränderungen der Einflussfaktoren mit kurzfristigen, flexiblen Änderungen zur Anpassung der bestehenden Produktionsstruktur. Kurzfristige Änderungen sind oft kostspielig und ihre tatsächlichen Effekte nicht vorhersehbar. Langfristige Potentiale dagegen liegen in der Implementierung wandlungsfähiger Strukturen. Seit September 2010 wird im Verbundforschungsprojekt „Planung und Optimierung wandlungsfähiger globaler Wertschöpfungsnetzwerke (POWer.net)“, das vom Bundesministerium für Bildung und Forschung (BMBF) gefördert und vom Projektträger Karlsruhe (PTKA) betreut wird, ein Ansatz zur Konfiguration wandlungsfähiger Netzwerke erarbeitet. Dieser Fachbeitrag beschreibt einen systematischen Leitfaden zur Ist-Analyse existierender Wertschöpfungsnetzwerke mit Blick auf die anschließende Konfiguration wandlungsfähiger Strukturen. Im Mittelpunkt stehen neben relevanten Informationen zum Zeitpunkt der Ist-Analyse auch Inhalte für die Identifikation zukünftiger Wandlungsbefähiger und Wandlungstreiber.

Um Handlungsempfehlungen zur Auslegung robuster Produktionssysteme geben zu können, muss zunächst die Leistungsfähigkeit eines Produktionssystems bei Veränderung stochastischer Einflussgrößen (beispielsweise Nachfrageschwankungen oder Materialverknappung) untersucht werden. Zur Leistungsanalyse eignen sich unter anderem analytische und simulationstechnische Ansätze. Dieser Fachbeitrag beschreibt ein hybrides Analyseverfahren, bei dem die Simulation von komplexen Produktionssystemen zur Reduzierung von Simulationszeit und -aufwand an zweckmäßiger Stelle durch analytische Teilberechnungen ergänzt wird. Entwickelt wird die hybride Modellierung seit Mai 2010 in einem interdisziplinären Projekt des wbk Institut für Produktionstechnik und des Institut für Fördertechnik und Logistiksysteme (IFL) des Karlsruher Institut für Technologie (KIT). Die Forschungsarbeiten werden von der Deutschen Forschungsgemeinschaft (DFG) gefördert.

Eine global agierende Produktion verlangt den weltweiten Einsatz von Produktionstechnologien unter differierenden standortspezifischen Rahmenbedingungen. Zur optimalen Nutzung der jeweiligen Standortvorteile ist eine individuelle Anpassung in vielen Fällen sinnvoll, jedoch oftmals aufgrund produktseitiger Vorgaben oder strategischer Ausrichtungen nicht umsetzbar. Vor diesem Hintergrund ist es wichtig, eine Entscheidungsunterstützung zur richtigen Produktionstechnologieauswahl zur Hand zu haben. Einen Ansatz hierzu bietet eine neu entwickelte Methode zur Identifikation der mit einem Technologietransfer verbundenen standortspezifischen Risiken und Chancen. Global Technology Roadmap - Location-related production technology evaluation for risk minimization and increasing the opportunities in the case of commitments abroad Globally active production logically entails the worldwide use of production technologies under differing location-specific boundary conditions. Individual adaptation makes sense in many cases in order to exploit the advantages of the respective location in an optimum manner. This can, however, often not be realized due to product-related specifications or strategic orientations. Against this background, it is important to have a decision support system at hand in order to be able to select the appropriate production technology. An approach for the identification of the location-specific risks and opportunities associated with technology transfer is offered by this method.

Die zunehmende Variantenvielfalt ist eine Herausforderung bei der Kapazitätsabstimmung von Fließmontagelinien. Kurzfristige Veränderungen der Produktionsaufgabe sind eine Herausforderung bei der Umsetzung effizienter Prozesse. Durch die Anhäufung zeitintensiver Werkstücke können Situationen auftreten, in denen Arbeitsplätze überlastet werden. Die Daimler AG entwickelte in Zusammenarbeit mit dem Institut für Produktionstechnik (wbk), Karlsruhe, eine Methode auf Basis eines Warteschlangenmodells, um Auswirkungen von Veränderungen des Produktionsprogramms frühzeitig zu bewerten.

Small and medium-sized companies encounter enormous difficulties when trying to implement lean production methods according to the role model of the Toyota Production System. This is caused by the varying effects of lean methods on production figures depending on the production conditions concerning product variety and volumes, variation of process and set-up times, etc. This article presents approaches developed at the Institute of Production Science (wbk), Karlsruhe Institute of Technology, to evaluate and optimize the effects of lean methods in small series productions based on the quantified interdependencies with the relevant target figures. It enables the best combination of lean methods to be identified and recommendations for the efficient implementation of these lean methods.

Die Kenntnis der Messunsicherheit ist speziell bei der Qualitätssicherung von Bauteilen im Mikrometerbereich wesentlich. Dies hat seinen Grund in den bei Mikrometerbauteilen in Relation zur Bauteilgröße großen Formabweichungen sowie den engen Spezifikations -grenzen. Der Fachartikel befasst sich mit den aktuellen Arbeiten am wbk - Institut für Produktionstechnik - zur Abschätzung der Mess -unsicherheit, zum Einfluss der Messunsicherheit auf die Prozessfähigkeit sowie zur Wirkung von Formabweichungen auf die Messunsicherheit im Mikrometerbereich.

Zunehmend rücken große produzierende Unternehmen die Folgekosten der von ihnen beschafften Produktionsmittel in den Fokus ihrer Beschaffungsentscheidung. Diese Entwicklung stellt aber sowohl die Betreiber selbst als auch die Hersteller der Produktionsanlagen vor große Herausforderungen. Am wbk Institut für Produktionstechnik des Karlsruher Instituts für Technologie (KIT) wurde daher ein Forschungsschwerpunkt „Life Cycle Performance“ (LCP) etabliert, welcher diese Entwicklung zur Betrachtung des gesamten Lebenszyklus von Investitionsgütern wissenschaftlich begleitet und sowohl die Betreiber als auch die Hersteller dabei unterstützt, Vorteile aus ihr zu ziehen.

For the enhancement of technical workpiece surfaces with even larger dimensions, the application of microstructures on the surface is an appropriate way to improve the fitness for use without changing the properties of the basic material. Considering the extremely small dimensions of approximately 5–20 μm of the applied microstructure, the quality assurance faces new challenges related to the obtainment and evaluation of measurement data. This article presents an approach for the automated detection of shape deviations of a microstructure, as well as the detection of measurement errors during an optical or tactile measurement. The explained algorithm is based on the analysis of the measurement points within a point cloud by observing the distances between the single points. To illustrate the disturbance in the measurement point cloud every point is evaluated by an adaptive weighting function. The weighting of each measurement point can then be visualized by plotting the whole point cloud according to a corresponding color scale. The suitability of the point cloud analysis is demonstrated by the examples of a shape deviation (artificial groove) and a measurement error, occurred by measurement via confocal microscopy.

Ausgehend von einer durchgeführten Studie über die Bedeutung der frühzeitigen Kostenkalkulation von Produktionssystemen unter Berücksichtigung von Varianten- und Stückzahlflexibilität wird eine am wbk Institut für Produktionstechnik entwickelte Methodik vorgestellt, um Produktionssysteme in frühen Planungsphasen monetär zu bewerten. Die Bewertung basiert auf einer Monte-Carlo-Simulation, die eine detaillierte Analyse der Kostenverläufe und der stochastischen Schwankungen über den Lebenszyklus eines Produktionssystems erlaubt.

Not every product can be successfully sourced in low-cost countries. Disadvantageous cost structures or extremely complex workpiece designs are the most frequent reasons for failures. A design that has been tailored to low-cost country sourcing offers the possibility of increasing potentials while reducing risks and costs at the same time. This paper highlights different possibilities to define the interface between product design and production in low-cost countries, identifies the factors influencing the design, deduces basic principles and illustrates guidelines for an adapted product design.

Ausgehend von der Automobilindustrie werden Methoden der Lean Production zunehmend in anderen Branchen und bei kleinen und mittelständischen Unternehmen eingesetzt. Zur Bewertung der Auswirkungen bei Übertragung und Einführung von Lean Methoden auf die komplexen Anforderungen der Kleinserienproduktion bietet sich die Simulationstechnik an. Um die simulative Produktionsplanung und -umgestaltung in kleinen und mittelständischen Unternehmen zu unterstützen, werden am Institut für Produktionstechnik (wbk) des Karlsruher Instituts für Technologie (KIT) Prozessmuster zur anwenderfreundlichen Abbildung von Lean Methoden in einer Simulationsumgebung entwickelt und implementiert.

An increasing product variety causes different cost effects in several divisions of a company. These effects have to be identified in order to compare them to potential revenues. However, at the time strategic market decisions have to be made, not all detailed information about product variants and quantities are available. Analyses of future cost development and the choice of the manufacturing system are difficult and uncertain. Within the framework of the project “VireS” a simulation algorithm was developed at the Institute of Production Science (wbk) to simulate future developments of life cycle costs of manufacturing systems depending on quantities and varieties in an uncertain environment.

Two different kinds of manufacturing technologies are used to produce micro systems or micro structures on macro-scale parts. MEMS (micro-electro-mechanical systems) are produced by using bottom up techniques such as lithography, etching and bonding, which were adopted from well established microelectronic manufacturing processes. Precision Engineering systems apply a top-down approach and use very precise versions of conventional manufacturing techniques such as milling, turning or powder injection molding to produce micro-mechanical parts. At the present time, both technologies face the challenge of long iterative product development cycles before the functionality of the product and the set-up of the production system can be verified. A structured, systematic, and rational design approach including the verification of both the product’s functionality and its efficient manufacturability is necessary to enable the fast development and cost-effective production of so-called killer applications. Even though both approaches offer complementary advantages concerning the range of materials, design flexibility and the capability to produce parts in small and large volumes, there have been no attempts to integrate the two technologies up to now. Through the framework of axiomatic design, this paper proposes a structured approach to derive and simultaneously verify micro systems and the necessary manufacturing processes by applying and integrating both Precision Engineering and MEMS techniques.

Die automatisierte und flexible Bearbeitung gekrümmter Strangpressprofile in der Kleinserienfertigung ist im Bereich der Arbeitsvorbereitung mit einem erheblichen zeitlichen Aufwand verbunden. Im Rahmen des Sonderforschungsbereiches Transregio10 (SFB/TR10) wird eine Prozesskette zur flexiblen Herstellung und Bearbeitung räumlich gekrümmter Profile entwickelt und umgesetzt. In diesem Artikel wird die flexible Programmierung der prototypisch realisierten Maschinentechnik vorgestellt.

The configuration of Value Added Networks consisting of globally distributed locations of a company and its partners and suppliers is a long-term decision and therefore subject to high dynamics and uncertainties. Furthermore the evaluation of different network configurations has to be done with respect to the underlying multidimensional target systems. This paper describes an integrated concept for the evaluation of network configurations using a discrete-event simulation tool with an integrated Monte-Carlo-Simulation to include dynamics and uncertainty and the PROMETHEE approach for the consideration of multidimensional target systems. The concept leads to robust network designs, which are adjusted to the companies needs.

Manufacturers of production facilities must not only be able to support their customers actively throughout the life cycle by optimizing machines and productivity but also by establishing a profitable environment for product-accompanying services. Therefore, a method has been developed which allows for the calculation of the costs of service contracts during the offer phase. Subject to different influencing variables which are deposited with stochastic distributions, the costs will be determined by the Monte Carlo method. The Monte Carlo method is used to estimate uncertain forecasts.

Technische Dienstleistungen gewinnen in der Maschinenbaubranche immer mehr an Bedeutung. Allerdings ist der quantitative Nutzen, z.B. in der Phase der Vertragsgestaltung, oft sehr schwer zu bestimmen. In diesem Artikel wird deshalb ein Ansatz für eine Kosten-Nutzen-Analyse technischer Dienstleistungen vorgestellt. Die Berechnung der Kosten und des Nutzens, gemessen anhand der Verfügbarkeitssteigerung durch technische Dienstleistungen, basiert auf der Simulation des Maschinenausfallverhaltens sowie zugehöriger Reparaturprozesse über einen gegebenen Zeitraum.

Genauigkeitssteigerung einer integrierten Prozesskette zur Fertigung leichter Tragwerkstrukturen Im Rahmen des Sonderforschungsbereichs SFB/TR10 wurde eine Prozesskette zur flexiblen Herstellung und Bearbeitung dreidimensional gerundeter Strangpressprofile entwickelt und prototypisch umgesetzt. In diesem Fachaufsatz werden die Arbeiten zur Genauigkeitssteigerung in den Prozesseinzelschritten sowie eine Methode zur Vermessung und Markierung der hergestellten Profile über einen bauteilimmanenten Maßstab vorgestellt. Flexible production of curved extrusion profiles - Increasing accuracy of an integrated process chain for the production of lightweight frames The collaborative research centre SFB/TR10 is developing and setting up prototypical a process chain for the flexible production and machining of threedimensionally curved extrusion profiles. This paper presents the work aiming on increasing accuracy of selected process steps as well as a method for measuring and marking the manufactured profiles with the help of a part immanent scale.

Globally operating companies face the challenge of an optimal and efficient configuration of their value added network. The participating sites, partners, and suppliers have to be selected according to their specific capabilities. Thereby the configuration has to respect not only the actual status but also the different dynamic influences of the nodes of the network themselves and also of the connections between them. This paper presents an approach for the configuration of global value added networks using business capabilities with special consideration of the ramp-up behaviour of the single elements. A simulation implemented in Tecnomatix Plant SimulationTM serves as a validation for the theoretic approach.

The reliability of machine components depends on their operational conditions. In order to maximize this reliability, the preventive maintenance intervals and the provision of spare parts have to be adapted to the individual load collectives. Up to now, there has been for different machine components no comprehensive approach to quantify the effect of load collectives and to adapt the respective actions accordingly. This paper presents amethod which calculates the optimal time for preventivemaintenance and spare part provision by a stochastic optimization algorithm based on a load-dependent reliability model.

Flexible and automated small-batch production requires a high degree of facility adaptability for the product to be manufactured. Here spatially curved profiles pose a particular challenge in terms of the exact positioning and the assurance of component quality during the machining process. This paper describes the concept and implementation of a metrological approach to the positioning of spatially curved tube profiles for profile machining. Single laser markings put on the component surface are combined into a component-specific scale. The design of the markings is derived systematically considering the boundary conditions. The component-specific scale also constitutes the basis for an incremental identification of the profile contour, allowing for flexible inline quality assurance for almost any type of curved profile contours. Profile geometries can be described regardless of contours by means of cubic spline interpolation.

Oft müssen Hersteller von Produktionsanlagen sowohl den Kunden während des Lebenszyklus aktiv durch die Optimierung von Maschinen unterstützen als auch ein wirtschaftlich attraktives Portfolio produktbegleitender Leistungen bereitstellen. Für dieses Umfeld ist eine Methode zur Kostenkalkulation von Instandhaltungsverträgen während der Angebotsphase entwickelt worden. Die Kosten werden mittels der „Monte-Carlo-Simulation“ ermittelt und sind durch verschiedene Einfluss‧variablen beeinflusst, die sich über stochastische Verteilungen bestimmen lassen.

Die bei vielen großen Unternehmen erfolgreich eingeführten Lean Methoden können nicht unangepasst auf die Einzel- bzw. Kleinserienproduktion übertragen werden, da sie sich je nach Anwendungsumfeld unterschiedlich auf relevante Produktionskennzahlen wie Bestand, Durchlaufzeit, Maschinenverfügbarkeit, Ausschussrate etc. auswirken. Der Artikel behandelt die Fragestellung, welche Lean Methoden in welcher Ausprägung für spezifische Anforderungen in der Kleinserienproduktion auf Basis quantifizierter Wirkzusammenhänge geeignet sind.

Der Fachaufsatz beschreibt ein am wbk Institut für Produktionstechnik der Universität Karlsruhe (TH) entwickeltes Spannkonzept für die flexible Bearbeitung räumlich gekrümmter Profile. Anhand elementarer geometrischer Überlegungen wird der Aufbau der umgesetzten Spanntechnik hergeleitet. Es wird ein Ansatz vorgestellt, welcher die Genauigkeit der Profilpositionierung in der Spanntechnik mit auf der Profiloberfläche aufgebrachten Markierungen erhöht. Die Beschreibung eines Vorversuchsstandes sowie der ersten Ergebnisse zur Markierungsdetektion mittels digitaler Bildverarbeitung runden das Thema ab.

This article describes a clamping concept for the flexible machining of spatially curved profiles developed at the wbk Institute of Production Science of the Universität Karlsruhe (TH). Simple geometrical considerations form the basis of the prototypically implemented clampingsystem design. The approach presented in this article allows for accuracy improvements regarding the positioning of the profile in the clamping system on the basis of markings applied onto the surface of the profile. Besides, the preliminary test rig set up and first results on the detection of themarkings by means of digital image processing are presented.

Micro manufacturing processes are characterized by high process variability and an increased significance of measurement uncertainty in relation to tight tolerance specifications. Therefore, an approach that separates the superposition of measurement and manufacturing variation is demanded. A novel design for a quality control chart that makes it possible to monitor, control and extract measurement variation from manufacturing variation is proposed. Thus, a definite cause diagnosis on the approval or rejection of micro components due to errors either in the measurement or in the manufacturing process is possible. The proposed multivariate µ-EWMA chart which is based on weighting each measurement data with its current measurement variation is discussed and benchmarked with traditional control charts.

Micro production, with an annual forecasted growth rate of 20 per cent will clearly be a key technology of the 21st century. High-precision engineering, which uses miniaturized conventional manufacturing techniques, e.g. milling, turning, and drilling, has significant potential for application to the manufacture of micro-sized products with exacting precisionand accuracy requirements. Owing to its flexibility and its ability to produce complex three dimensional geometric shapes in a broad variety of different materials, micro cutting is ofspecial importance both for small scale and mass production environments. However, cutting in micro dimensions follows special rules caused by size effects. Successful micro cutting depends on statistically reliable and robust processes and therefore on knowledge about parameter adjustments and process characterization. Statistical analyses of experimental micro cutting data and modelling studies are used to study the effects and interactions of process parameter variations for workpiece material, cutting edge radii, cutting speed, depth of cut, and application of a lubricant. The results show a significant influence of most of the mentioned factors on the response variable surface roughness and specific cutting force. Based on the experimental data and the statistical modelling studies, linear models for the specific cutting force and surface roughness are proposed. In addition, the outcome is compared to theempirical cutting model of Victor-Kienzle derived for application in macro dimensions.

Bei der Konfiguration von globalen Wertschöpfungsnetzwerken muss die Anlaufphase aufgrund der hohen wirtschaftlichen Relevanz explizit Berücksichtigung finden. Ausgehend von dieser Notwendigkeit stellt der Fachbeitrag ein Konzept vor, mit dem die Anlauffähigkeit eines potentiellen Wertschöpfungsnetzwerks anhand der Qualitätsfähigkeiten der einzelnen Wertschöpfungsknoten (interne Standorte und externe Partner) bestimmt werden kann.

This paper introduces a new approach to handle and machine spatially curved profiles using a flexible and intelligentclamping system. Firstly, requirements to the clamping system are specified which have to be fulfilled for a flexible smalland medium batch production of light-weight frame structures. Subsequently, the design of the flexible clamping systemis described. To maintain a once reached condition of order over the entire process chain, an in-line measuring systemhas to be integrated. Several metrological processes have been tested regarding their application on spatially curvedprofiles. To allow an exact positioning and orientation of the profiles within the clamping system for machining andhandling, additional marks were placed on the profile surface in well-defined distances. The functionality of thispositioning and orientation process will be illustrated in dependence on the gaging process of an incremental measuringsystem. Also, an outlook to an extended use of the part-specific scale for an integrated quality assurance is given.

With a novel extrusion process which is investigated in the Collaborative Research Center Transregio 10 (SFB/TR10), it is possible to manufacture spatially curved aluminum profiles. This process is the base for an automated small and medium size batch production of light-weight frame structures. For the handling and machining of the spatially curved profiles, highly flexible machines and manufacturing equipment are needed. Today’s automated process chains do not reach a sufficient flexibility.This article introduces a new approach to handle and machine spatially curved profiles using a flexible gripping and clamping system. Firstly, the requirements concerning the process comprehensive gripping technology, which have to be fulfilled for a flexible small and medium batch production of light-weight frame structures, are specified. Subsequently, the function and design of a flexible gripping and clamping system are described. Furthermore, metrological processes to maintain a once reached condition of order during the entire process chain are depicted.

Decreasing product life-cycles and resulting market pressure to launch new products in a high frequency are describing today’s automotive industry. Therefore production ramp-ups are gaining more and more importance. Production ramp-ups are characterized by instable business-processes within the organization, new products and new production technology. This combination often causes quality and availability problems which are the main challenges for a product launch in time and costs. Thus, fast reactions to quality and availability problems are crucial for competitiveness. In this paper, a new simulation based decision support system for production ramp-ups is presented. The system allows the simulation of influences on technically critical processes under the dynamic environment of a production ramp-up. Next to the theory, so called quality simulation, a prototypical implementation and simulation results are presented.

Kundenindividuelle Produkte sowie steigender Wettbewerbs- und Kosten druck in Verbindung mit sich stetig verkürzenden Produktlebenszyklenbegründen die Bedeutung des Produktionsanlaufs für produzierende Unternehmen [1]. Ein effizienter und effektiver Produktionsanlaufgestattet einen erfolgreichen Markteinstieg, kann „Lost Sales“ vermeiden helfen und bildet eine Basis für den finanziellen Erfolg des Produkts und des Unternehmens [2]. Dieser Fachbeitragkonzentriert sich auf eine frühe Phase des operativen Produktionsanlaufs („Inbetriebnahmephase“) und zeigt eine methodische Unterstützung zur Konfiguration und Planungssystematik von Abnahme -prozessen. Durch die modifizierte Anwendung eines Verfahrens aus dem Operations Research wird eine zeitliche Verkürzung der Inbetriebnahmephaseerreicht. Damit stellt sich ein Kostenvorteil im gesamten Produktionsanlauf ein. In diesem Beitrag wird ein Job-Shop-Problem modelliert und damit die Reihenfolge der Maschinenabnahmeschritte optimiert.

Die Globalisierung, aus der neue Märkte mit unterschiedlichen Standortbedingungen und Lohnkostenniveaus hervorgehen, sowie der steigende Zeit-, Kosten- und Flexibilitätsdruck führen zu einer zunehmenden Dezentralisierung der Wertschöpfung. Ein wesentliches Bewertungskriterium für dadurch entstehende dezentrale Wertschöpfungsnetzwerke stellt die Fähigkeit der einzelnen Wertschöpfungspartner zu einem schnellen und kosteneffizienten Anlauf dar. Dieser Fachbeitrag skizziert ein Lösungskonzept zur Konfiguration von Wertschöpfungsnetzwerken unter besonderer Berücksichtigung der Anlaufkosten.

Research in micro production technology mainly focuses on the development and optimization of a dedicated manufacturing process. However, for industrial application, it is of foremost importance to know which alternative technologies are capable of manufacturing a specific work piece or a specified quality feature and which of these technologies are the best to choose. By means of altered quality function deployment (QFD) and a web based structure catalogue, different micro manufacturing technologies such as micro milling, laser ablation and Electric Discharge Machining (EDM) have been benchmarked concerning their capabilities to fabricate micro molds consisting of wear-resistant materials. Besides process comparison with regard to accuracy and efficiency, the new architecture of the House of Quality of the QFD facilitates the identification and optimization of critical process parameters. Furthermore, by means of the developed structure catalogue, the verification of machinability of product designs is assured.

Die Planung und Durchführung des Produktionsanlaufs sind aufgrund der verkürzten Produktlebenszyklen und der stetigen Erweiterung der Produktpalette ein wesentliches Erfolgskriterium für Unternehmen. Charakterisiert ist der Produktionsanlauf durch instabile Produktions prozesse, die Qualitätsprobleme und Zeitverluste ver - ursachen. Dieser Fachbeitrag zeigt das Konzept einer simulationsbasierten Anlaufunterstützung. Sie erlaubt die Bewertung des in - stabilen Produktionssystems sowohl hinsichtlich Qualitätsfähigkeit als auch Mengenleistungsfähigkeit.

The ramp-up of a new production system has become a decisive factor influencing profif. The reason is an incessantly growing product range with constantly decreasing life cycles. Characterisfic for ramp-up processes are insfable production processes, that Iead to a !arge number of quality problems. The approach of Quality Simulation presented in this paper allows simulafing the insfable stafe of a production sysfem during ramp-up. Thus, the produclion planner is supporled during both ramp-up planning and 1he actual ramp-up period. Using Quality Simulation the planner can idenlify deviations from the target ramp-up curve at an early stage.

The modular design of load-bearing structures out of precast concrete compo-nents offers considerable potential for more efficient and sustainable construction. A new concept of individual assembly can be used by compensating dimensional deviations of the individual modules through selective positioning of the components within the struc-ture. The quality of the resulting structure depends on the combination of all component dimensions. In this paper, an adaptive process control for production is presented which aims at an optimal result over all components of the structure. Such a cross-component process control has not been considered in literature yet, since components of a product are only considered individually so far. The paper furthermore considers that the compo-nent dimensions depend in an unknown and stochastic way on certain setting parameters of the production process. By using active sampling to vary the setting parameters adap-tively during production, knowledge about the transfer function can be gained efficiently. In particular, the heat treatment process for ultra-high performance concrete components is considered as use case. A cross-component process control is presented, which itera-tively approximates the transfer function of the manufacturing process during operation by means of regression. Different strategies for the selection of parameter settings are developed, optimized and compared by simulation. In comparison with a benchmark strategy based on complete information, it can be shown that good results can be achieved by selected strategies depending on the overall number of components considered.

Die Automobilindustrie steckt in einem Transformationsprozess ungeahnten Ausmaßes und Ausgangs. Ob durch striktere europäische Abgasgrenzwerte, den Zwang lokaler Emissionsfreiheit oder den Druck des chinesischen Marktes beim Kampf um eine neue Vor-herrschaftsrolle - die Gründe deutscher Automobilisten zur Elektrifizierung sind vielschichtig und die Folgen kaum abschätzbar. Die Frage, ob neue Antriebstechnologien in den Markt eingeführt werden, stellt sich mittlerweile kein Automobilhersteller mehr, stattdessen verbleibt die Frage nach dem ?wie?. Mit der diesjährigen wbk Herbsttagung ?Auf dem Weg zur Elektromobilität ? Wettbewerbsfaktor Produktionstechnik? wollen wir die vorhandenen Chancen im Bereich der Produktionstechnik für die Elektromobilität aufzeigen und einen Beitrag dazu leisten, dass diese auch genutzt werden. Hochkarätige Impulsvorträge aus Industrie und Forschung schaffen die Diskussionsbasis für einen Informationsaustausch zur Elektromobilität. Die wbk-Herbsttagung bietet dabei eine Plattform für den Dialog zwischen Politik, Anwendern, Produzenten, Anlagenbauern sowie dem wbk als Forschungspartner vor Ort.

In the current VUCA-world (Volatility, Uncertainty, Complexity & Ambiguity) collaboration is a potent method to increase the efficiency of slug-gish, historically grown global value added networks and, thus, face the resulting new challenges. Although the different benefits of collaboration, within as well as between different companies, are already well known, the collaboration level is not reaching its potential. At the same time the production principles are dis-rupted by digitalization. The influences of the digital era can be noticed by the increasing servitization of manufacturing. Therefore, the state of the art needs to be updated in order to illustrate the new conditions. Especially services will have a big impact on the way how companies interact with each other. In this article an approach is presented to classify different Smart Services regarding different properties and the resulting requirements for realization. This framework is a premise for the goal to reevaluate collaboration scenarios based on Smart Ser-vices and, therefore, a premise for a higher level of collaboration in global value added networks.

Individualized products and timely delivery require agile just-in-time manufacturing operations. Scheduling needs to deliver a robust performance with high and stable results even when facing disruptions such as machine failures. Existing approaches often generate predictive schedules and adjust them reactively as disturbances occur. However, the effectiveness of rescheduling approaches highly depends on the available degrees of freedom in the predictive schedule. In the proposed approach, a centralized robust scheduling procedure is coupled with a decentralized reinforcement learning algorithm in order to adjust the required degrees of freedom for a maximally efficient production control in real-time.

Strategic management of global production networks (GPN) is getting increasingly complex and continuously more relevant for the long-term success of producing companies. Each plant in the GPN needs to accomplish goals coming from strategic management to stay competitive by adjusting their plant capabilities. In tactical management, production ramp-up processes are a great chance to be used for adjusting plant capabilities due to the high investment and cost determination character. This paper faces the possibility to integrate production ramp-up processes in the strategic management of GPN. The approach identifies relevant ramp-up dimensions and processes for an early strategy achievement.

Modern production systems tend to have smaller batch sizes, a larger product variety and more complex material flow systems. Since a human oftentimes can no longer act in a sufficient manner as a decision maker under these circumstances, the demand for efficient and adaptive control systems is rising. This paper introduces a methodical approach as well as guideline for the design, implementation and evaluation of Reinforcement Learning (RL) algorithms for an adaptive order dispatching. Thereby, it addresses production engineers willing to apply RL. Moreover, a real-world use case shows the successful application of the method and remarkable results supporting real-time decision-making. These findings comprehensively illustrate and extend the knowledge on RL.

In the course of digitalization many small and medium-sized companies face the challenge of using the existing database for process optimization in manufacturing. Furthermore, the demand-oriented expansion of the database is a great challenge. A lack of competencies, limited financial resources and historically grown data structures, which show a strong heterogeneity and lack of transparency, are the central obstacles. A specific approach, how data analytics projects for process optimization should be carried out in manufacturing, is presented. In particular, the question which sensors should be implemented to expand the database is answered. The approach is applied exemplarily for a manufacturing line.

Companies struggle to overcome the difficulties stemming from the dynamic environment of global production due to the specific conditions in different regions. Particularly, insufficient know-how about a regionalized implementation strategy of smart automation (SmAu) technologies is one significant difficulty for enterprises. Thus, developing a key performance indicator (KPI) oriented, regionalized implementation strategy for smart automation technologies is increasingly important. In this context, a new approach is exposed to systematically investigate and identify the interdependencies among location factors, smart automation technologies, and KPIs. Firstly, the environment consisting of location-related factors, KPIs and smart automation technologies is defined in detail. Further, a Catalog quantifies the influence of different regions in China. Secondly, important aspects to model the qualitative and quantitative interdependencies in a multimethod simulation are introduced. Subsequently, an approach to analyze suitable implementation strategies is presented. A case study based on a production line for digitalized production technology is used to validate the proposed approach.

Today, companies of all industries are part of global production networks. They have a variety of performance relationships with suppliers and customers. Digitalization offers the potential to exchange more information between the partners of global production networks. This may improve operational performance. Especially within the three business processes order management, quality problem solving and engineering change management, a targeted increase in transparency promises a better handling of disruptions and an increase in robustness. This paper presents a simulation-based methodology for modeling production and business processes as well as information exchange in global production networks. Following the principles of Design of Experiment (DoE), screening test plans first carve out the impact of disruptions and information exchange on the performance of the production network. This is followed by the determination of the disruption-robust information exchange using Taguchi-experiments. Starting from the actual state of information exchange, digitalization activities to increase transparency are finally determined. The activities consist of the implementation of digitalization technologies and the stronger linkage of information systems. The paper ends with an application of the methodology to a global production network for plastic-metal components in the automotive supplier industry.

Shorter product lifecycles lead not only to faster time-to-market for products but also to the need for just as fast available associated production systems. These shorter product lifecycles, as well as the increasing individualization of products, also result in further decreasing production lot sizes. Young companies in China in particular are characterized by a very high speed of innovation but may not have the necessary manufacturing knowledge or capacities to bring their developed products to the market with a scalable production. For this reason, there is a great need to quickly set up and commission turnkey production systems or to reconfigure existing production systems for new production tasks in the shortest possible time. This paper describes the design and architecture of a cloud platform with the aim to support a manufacturer independent design process for turnkey production systems. This process ranges from the product to be manufactured to the operation of the production system. Firstly, the structure and methodology used to link the various objectives are discussed. The system for recording and structuring product and production system data to create reusable modules from components and machines is described. Subsequently, the use of standardized modules is developed to support reconfiguration of the production system during operation. In addition, the digital business models tailored to the production system are proposed to the platform user for commissioning and operation of the plant. A case study is conducted to validate the proposed methodology.

Bottlenecks in production lines are often shifting and thus hard to identify. They lead to decreased output, longer throughput times and higher work in progress. Go & See is a well-established Lean practice where managers go to the shop floor to see the problems first hand. Mixed reality is a promising technology to improve transparency in complex production environments. Until recently, mixed reality applications have been very demanding in terms of computing power requiring high performance hardware. This paper presents an approach for real-time KPI visualization using mixed reality for bottleneck identification in production lines relying on the bring-your-own device principle. The developed application uses image recognition to identify work stations and visualizes cycle times and work in progress in augmented reality. With this additional information, it is possible to discern different root causes for bottlenecks, for example systematically higher or varying cycle times due to breakdowns. This solution can be classified according to the acatech industry 4.0 maturity model as a level 3 - transparency - application. It could be shown that the identification of bottlenecks and underlying reasons has been improved compared to standard Go & See.

Additively manufactured (AM) workpieces, which have been produced by means of laser beam melting (LBM), tend to show quality relevant pores and cracks on the inside. Quality assurance on these parts may be conducted using x-ray Computed Tomography (CT), as CT is able to spot pores and cracks in the entire volume of a specimen. However, the uncertainty of detection of such cavities in a CT measurement is unknown. To tackle this shortcoming, different authors have compared metallographic cross sections to CT images. None of these investigations have compared the cross section?s plane directly to the corresponding plane of the CT?s 3D voxel image, without using features of the CT image itself, though. This paper introduces a special artifact as reference standard, whose pyramid like form allows a direct comparison of a metallographic cross section and the corresponding plane in a CT scan. The shape of the test object allows to calculate the parameters of the plane equation of the metallographic cross section in a coordinate system fixed to the test object. The plane equation is used to identify and investigate the corresponding plane in the CT scan. By comparing this artificial cross section from the CT scan with the cross section from the metallography specimen, the CT?s performance for detecting pores is assessed. As a result, a general method to test any CT?s capability to detect pores in an AM part is given by using cross sections of test objects with the proposed pyramid like form.

Increasing complexity and dynamics in globally distributed supply chain networks makes companies vulnerable to disruptions and does not only require good and robust planning, but also rapid troubleshooting as a reaction to unforeseen events. However, companies often neither possess a targeted approach for the systematic identification and communication of disruptions nor for the appropriate reaction to a disruption and the minimization of its consequences while considering the entire supply chain. Hence, this paper proposes a framework for reactive disruption management which allows for a multi-criteria evaluation and logical selection of measures in case of a disruption.

As a result of the increasing interdependencies within global production networks, the importance of an improved coordination of the associated individual processes is continuously rising. In particular, enormous potential is expected from a stronger integration of production and logistics planning and control. While previous approaches have mainly dealt with the integration of production planning and distribution logistics planning, this paper pursues the goal of integrating the procurement logistics and the production perspectives, considering both predictive and reactive components. To achieve this goal, an initial framework for the integrated procurement logistics and production planning and control is developed and exemplified in the context of an aircraft manufacturer within the scope of this paper.

Operational management of global production networks is challenged by disruptions which result e.g. in order changes, quality problems and engineering changes. Their negative impact on performance may be reduced by a more intensive exchange of information between the network partners. Digitalization offers many new measures for such an increase of transparency. However, the interactions, the optimal level and the realisation of a broader information exchange define a challenging decision problem. This paper improves operational performance of production networks by applying multimethod simulation, statistical experiments and metamodeling techniques to identify a state of information exchange which is robust to disruptions.

Pulse-phase thermography (PPT) is widely used to nondestructively inspect internal defects in fiber reinforced polymers. However, the challenges using PPT for complex shapes is poorly documented in literature. Only small changes in the object distance have been considered. Complex parts can have significant variations in object distance and thus, in detected radiation. In this contribution, the effect of a non-orthogonal camera angle with respect to a flat sample, leading to varying object distances and an inhomogeneous sound background area in phasegrams, is investigated. Samples with artificial round and square defects of different sizes are positioned under varying angles with respect to the camera, representing geometric properties of complex parts. The construction of the thermographic system and the experimental setup to systematically vary the angle between camera and specimen is presented. We investigated the change of the signal-to-noise ratio (SNR) of artificial delaminations in PPT measurements under varying object distances. The SNR in a distance of 136 mm out of the focal plane is sufficiently high for image feature extraction. Phasegrams are exported to a colored representation, leading to a higher contrast in distinct color channels. An algorithm which extracts and merges defect information from three different color channels is developed. Challenging lighting conditions lead to a noisy background having artifacts. The developed filter performs better in defect detection and size quantification than a global or local threshold in grayscale phasegrams under those conditions.

Digital twins offer great opportunities in various domains of the product engineering process. However, current approaches to the use of digital twins only focus on different separated disciplines. In contrast to that, it is expected that the holistic use of digital twin models in product development and production will dominate future product generations, because they allow to create high-performance products competitively. This paper explores important challenges and future potentials of digital twins and Industry 4.0 for the seamless integration of product specification and production. In this regard, approaches of linking digital twins to other domains open up new possibilities in tolerance allocation and production integration. Thereby, the most efficient product specifications in technical and economic terms are achieved for the manufacturer. In addition, the connectivity of Industry 4.0 broadens the scope and enables the evaluation of alternative approaches in production planning and control. Approaches at the organizational level, product functions with specifications beyond the technological limits and production control strategies (e.g. order dispatching) ensure high performance operations. Simulations with a digital production twin with integrated digital product twin allow early estimations even before the actual ramp-up of the product. The future challenge addressed in this paper is to define a consistent framework for the holistic use of digital twins in the entire product development process, which requires the integration of product designers and production planner concepts.

Lightweight materials are materials of increasing importance. They offer the possibility to adjust specific stiffness and strength. Sheet Moulding Compound (SMC) in particular has been known for many years. Through a combination of discontinuous glass fibre SMC and continuous carbon fibre SMC, it is possible to set certain mechanical properties locally. However, a large number of defects can occur in the production of these materials. These include geometric deviations or delaminations. Not all errors can be detected within a reasonable time with only one measurement system. Therefore, in this work a multi-sensor system is developed which can detect both internal and external defects. It has been shown that a laser light section system is suitable for the detection of external defects. For internal defects, thermography offers great advantages. These two measurement processes are thus combined in one system. Both work quickly and can be fused in a further step. The laser light section process creates a cloud of points (CoP), which forms the basis for the thermography data. The 2D images of thermography are mapped to the CoP in a fusion step and thus converted into 3D images. The analysis of the phase images make it possible to determine the depth of the defects. Thus, this work offers the user a simple possibility to detect and localize defects in complex components. In a further step, the correlation between the defects and the mechanical effects is analysed in order to be able to make a statement about the effects of defects.

An increasing number of product variants and a decrease in demand certainty challenge manufacturing companies. Lean, flow-oriented production lines are best-practice to assure efficient production in a predictable environment. However, with the increase in complexity and uncertainty, more flexible production systems such as matrix production currently receive much attention. Having neither a common takt time nor a rigid linkage, they offer new degrees of freedom regarding process order and machine choice. This paper contributes to answering the question under which conditions a matrix production is favourable compared to a production line. To answer this question, the effects of MTTF and MTTR as driving factor to choose a matrix production over a production line are analysed. Regarding the material flow in the matrix, the benefits of routing flexibility and operation flexibility concerning throughput time, tardiness and output of the matrix production are evaluated. The results show that a rule based approach has its limits especially regarding the exploitation of operation flexibility. For low levels of routing flexibility, the rule based approach tends to generate sup-optimal solutions due to a lack of coordination between the agents.

X-Ray Computed Tomography (CT) has been successfully introduced into industrial applications in the last few years. Recent industrial needs aim at increasing the accessibility of CT technology to more users than only measurement experts. Suitable concepts for user support have been developed in the past. However, these user support concepts do not cover the entire measurement process and only a small variety of measurement tasks. To overcome these shortcomings and to support the user in an optimal manner, the existing concepts need to be integrated together with knowledge deduced from different measurements into a single software tool. In this paper, different types of knowledge based systems are compared and assessed in their ability to integrate knowledge of the measurement process, the form and material of the workpiece as well as quality parameters of the CT projections. The assessment is used to derive the structure of a suitable knowledge based system that addresses industrial needs regarding flexibility and usability. The results may be used in the future to develop a software tool for user support, which can be used in an industrial environment, enabling untrained users to utilize CT-based systems with a low measurement uncertainty.

Companies nowadays act in global production networks. These networks offer advantages such as production close to market as well as the exploitation of low factor costs. However, due to their interlinkage and complex structure, the resulting networks are characterized by a high susceptibility to disruptions. This paper presents an approach, which quantitatively examines the effects of disrupting events in production networks. The main focus of the study is on the question of how product quality is influenced by quality-related disruptions. To describe the analyzed relationships best, a Kriging based metamodel is adapted to the behavior of the developed multimethod simulation model. The results of the investigation are formalized causal relationships between the error probabilities in production networks, the inspection frequencies of the production systems involved, the respective generic network configurations and the observed PPM quality score.

Companies are confronted with increasing product quality requirements to manufacture high quality products, close to technological limits, in an economic way. The implementation of adaptive quality control strategies (QCS) in production offers an approach to cope with this challenge. In this paper, new function-oriented QCS by means of selectively assembling multiple components are demonstrated based on a functional product model. The implementation of QCS for fuel injector systems, which must fulfil narrow tolerances regarding the product’s functionality, show benefits in quality and cost-effectiveness. In the approach a functional model of the product and a simulation of the production system are implemented.

The current selective laser melting (SLM) process lacks both process quality and reproducibility. Recent research focuses on the integration of optical measuring technology, but acoustic sensors also seem promising. Initial results on acoustic methods show their suitability. The further processing of the data still shows difficulties, mostly due to the high sample rate. In this work a concept for an acoustic process monitoring system is developed and integrated into the process. First results show its capability to distinguish different process qualities. For this purpose, various configurations for in-process integration of acoustic measurement techniques are discussed and evaluated. The most promising structure-borne sound concept is integrated and tested in a test bed. In a Design of Experiments for specific parameter selection, cubes with different process qualities are produced, and the acoustic signatures are evaluated. For a first prove of concepts a Neuronal Network is trained to classify three different laser classes. Therefore, different NN topologies were tested and the best-found solution had a precision of more than 90%.

This paper provides a procedure to support organizations transforming towards Industry 4.0. We suggest that current models do not put sufficient emphasis on avoiding the development of redundant solutions and the focus on customer needs. The presented procedure therefore enables organizations to address the customer requirements with digital solutions without creating redundancy. A database of requirements an organization already fulfills and wants to see fulfilled in the future is set up by applying the user story method. These stories are tagged with attributes derived from literature. A clustering algorithm then analyses the stories in terms of similarity. This analysis reveals, first, redundant functions within the solutions and, second, suggestions about how to address unfulfilled requirements. The paper provides a case study in which the procedure is applied. The results show that large organizations already roll out redundant Industry 4.0 solutions and that the procedure can help avoiding them.

For the successful implementation of Manufacturing Systems 4.0 (MS4.0) in medium-sized companies, a structured introduction process is required. Main objective of this process is the analysis and evaluation of MS4.0 methods in order to select those that suit best for each company. The foundation of this process is a structure model to classify and describe MS4.0 methods. A subsequent analysis of interactions among the methods supports the identification and evaluation of effective implementation strategies. Thereby, a model based on system dynamics is applied. Based on the results, the methods are strategically and financially evaluated to select the MS4.0 methods suited for implementation. Finally, a method roadmap can be derived to support management for the strategic decisions in regards of MS4.0 methods.

Modern companies operate in global production networks. The operational performance of production networks is hampered by disrupting events. Digitalization and the horizontal interlinkage of production networks may increase information exchange and lead to more transparency. It is propagated as being an enabler for a faster identification and reaction to disruptions. This paper presents a metamodeling approach that maps disruptions as systematic parameter variations and analyzes their impact on the performance of production networks under different level of information exchange. The method aims for the determination of cause-effect relationships and contributes to the determination of the appropriate level of information exchange in production networks.

Due to shortened product lifecycles and an increasing number of variants, the need for scalable assembly systems is rising. This trend is even stronger in the production of emerging technologies. An important step in the planning of a scalable assembly system is the creation of system configurations. State of the art is a scaling of the system from a manual, over semi-automated to an automated system during the start of production. This process is very rigid and does not offer the flexibility which is necessary to react to highly volatile influencing factors. The authors have identified the urgent need for a thorough scenario analysis to adequately consider the risk in predicting volatile influencing factors. In this paper, a two-part methodology is proposed considering multiple scaling mechanisms allowing for a swift and cost-effective adaptation to external factors. The first part is concerned with the scenario analysis. In this part, the planner has to identify the volatile receptors that influence their production. For each of the identified receptors, market studies and workshops with internal experts are conducted to develop a detailed scenario analysis, modelled in a modified BPMN logic. In the second part, the planner needs to develop production system configurations according to the results of the scenario analysis. The appropriate scaling mechanisms are chosen based on the volatile receptors. The application of these mechanisms on station level results in various station concepts satisfying the entire range of expected values within the volatile receptors.

New emerging technologies challenge companies to adapt their product design and production processes constantly. This paper presents an approach that enables companies to manage new technologies by optimizing interdependent product design parameters and manufacturing technology chains. A product is modularized and modelled via parameter sets. Manufacturing technologies are described in a similar model. Possible manufacturing technologies for this product are identified and combined to technology chains. Based on a multi-criteria evaluation, critical product and manufacturing technology parameters are identified and the impact of adapting these parameters is quantified, thus enabling recursive optimization of product and manufacturing technology chain. Thereby, companies can manage new product and manufacturing technologies by assessing their implications and future potential.

In the context of Industry 4.0, the development of maintainable and scalable applications becomes a core activity to master for industrial companies. To offer convincing trainings, learning factories have to coordinate the development of IT and hardware solutions with training concepts. The development of maintainable, modular and stable IT solutions in coherence with the hardware is the basis for good trainings. Especially learning factories face the challenge to work with part-time staff that is unfamiliar with large IT and hardware projects, web technology or PLC programming and development methods. In this paper we present a model how to introduce agile methods step-by-step to teams that have to cope with the challenge of a new project paired with a new technology and development methodology without overloading the team. An adapted teaching concept to introduce these development methods has been developed. For each of the maturity levels, tools and processes are presented as well as criteria to indicate when the team is ready to pass to the next level. The paper also presents the results of an application of the model to the development team at the Learning Factory Global Production at wbk.

In geometrical measurements using computed tomography (CT), the measurement uncertainty is often derived from reference measurements that have been made with a tactile coordinate measuring machine (CMM). This paper shows the influence that a test object?s surface roughness has on such reference measurements. To do so, test objects which have been manufactured by means of additive manufacturing methods are compared to conventionally produced objects. Results of geometrical measurements using a tactile CMM as well as measurements conducted with a CT are analysed with respect to the surface quality. Following the analysis, the validity of tactile CMMs to reference CT measurements is discussed.

Equipment for selective laser melting (SLM) has mainly been developed for applications in rapid prototyping. This paper provides a methodology for a cost-oriented optimisation and planning of SLM equipment for series production lines. The approach thus supports the transition to more productive and cost-efficient equipment. The paper presents a two-step methodology: at first, setup time is reduced using heuristic rules based on the activity node network plan. Afterwards, the build-up time is optimised by cost and performance parameters like laser power and build chamber size. Using the presented methodology rules for a cost-oriented SLM-equipment can be derived.

In decision making problems regarding production network design, product variety oriented planning of network structures and capacities is indispensable. Due to increasing product variety, related planning tasks have become more complex to account for the significantly varying production requirements of product variants. To create a consolidated and expressive decision basis, a methodology to apply cluster analysis on product portfolios is developed in this paper. The introduced clustering method is able to handle production process-related binary data and production capacity-related metric data simultaneously. By applying this method, the product portfolio is partitioned into clusters so that variants within a cluster have similar requirements regarding production capabilities and capacities. The developed method is applied to two data sets resulting in more efficient and more accurate problem solving in comparison to established clustering methods.

The reduced time-to-market and multiple innovations lead to a rising number of emerging technologies and new products. Production systems for emerging technologies are subject to high stress from highly volatile influencing factors such as volume and variants. In order to react to these factors and to achieve cost-efficient production, companies need to establish scalable production systems. This paper introduces a methodology which supports the production planner with an iterative planning method for a scalable production system focussing on the scalability of the level of automation. The methodology consists of four steps. Its basis constitutes in a scenario analysis of the influencing factors for the production system. In the next step, alternative configurations of the production system are generated. From the different configurations, possible scaling paths are derived in accordance with the scenarios. The final step focusses on identifying the optimal scaling paths according to production cost and risk. The methodology will be demonstrated with the use case of fuel cell production within the European research project INLINE.

Companies are confronted with increasing product quality requirements to manufacture high quality products, close to technological limits, in a cost-effective way. Matching of assembly components offers an approach to cope with this challenge by means of adapted production strategies. To satisfy and optimize precise functionality requirements a model that integrates process variation and functionality is applied to enhance existing matching strategies. This paper demonstrates the implementation of functional models within production strategies for fuel injector systems. The injector system must fulfil high requirements regarding the functionality, i.e. providing a homogeneous fuel mixture at a constant level. To enhance matching strategies and the functional models for the assembled components, a machine learning algorithm will be applied. This model is utilized to determine and quantify a model for the functional relation between pre-process variations and product functionality and to optimize matching strategies by selecting the relevant features.

Introducing Manufacturing Systems 4.0 (MS4.0) is essential for the competitiveness of industrial companies. Nevertheless, their knowledge about the digitalization of manufacturing and the transition process is limited. This paper shows a structured way to plan, evaluate and implement MS4.0. This paper uses a three-step approach: In the first and second step different MS4.0 applications are structured and the interactions in between them are analyzed. The paper focusses on the third step, where a comprehensive method to evaluate different applications of MS4.0 and the Balanced Scorecard to support a coordinated and structured implementation of MS4.0 applications are introduced.

Lightweight material became more and more important during the last years. To ensure a defect-free production, effective measurement solutions for quality assurance are necessary. The Laser stripe sensors enable the evaluation of form deviations. For the detection of internal defects thermography provides a suitable solution. On this account the combination of these two non-destructive testing principles gives an opportunity to detect different kinds of defects regarding the outer geometry and the material within the parts. This paper deals with varied concepts to combine laser stripe sensor system and thermography and shows the potential of these methods.

Introducing Manufacturing Systems 4.0 is essential for the existence of competing industrial companies. Nevertheless, knowledge about benefits of Manufacturing Solutions 4.0 is limited. This paper introduces an approach to evaluate Manufacturing Systems 4.0. Uncertainty is integrated via fuzzy set theory and stochastic models. The financial impact of non-monetary criteria is directly modelled. A Monte-Carlo Simulation aggregates criteria in a probability distribution of the projects net present value (NPV). Comparing distributions of different alternatives determines the most favorable alternative and analyses potential and risk. Through this concept understanding of Manufacturing Systems 4.0 is improved and their benefits are displayed comprehensively.

Series vehicle production is designed to produce effectively at a defined number of vehicles per period. Regarding market forecasts the overall market trend depicts an increasing demand for electrified vehicles within an uncertain propulsion concept vehicle mix. This demand cannot be predicted precisely because of volatile influencing factors such as governmental subsidies. Automotive companies are therefore confronted with the challenge of rapidly adapting their production systems accordingly. An approach to handle the variety of models within vehicle final assembly is to establish mixed model assembly lines. Since single model assembly lines are optimized for a specific production volume of one model, the subsequent integration of vehicles using alternative propulsion concepts into single model assembly lines stands as a great challenge in final assembly. Moreover, producing with optimal configured assembly systems after integrating an additional model is not ensured further on. To address this challenge, an approach for the greenfield planning of assembly lines using the concept of changeability is presented within this paper. The presented approach offers a new method to cover uncertainty regarding the future propulsion concept mix of assembly lines. This affects the initial setup of an assembly line concerning the line balancing and assembly equipment as possible subsequent changes to the assembly system increase costs. The target conflict is to minimize changes to the assembly system due to the integration of further propulsion concepts while ensuring cost efficient assembly. Hereto, the line balancing problem is solved for a fixed production volume ratio using a developed optimization algorithm. Thereafter, the production volume ratios are varied in order to identify an optimal solution for line balancing and assembly equipment. The uncertainty of volume ratios is considered in the integrated costs calculation module.

Professional action-related competence of employees plays an increasingly important role for globally operating manufacturing companies to remain competitive. Furthermore, the Bologna process calls for a paradigm change in higher education by placing greater emphasis on the learning process and learner. In order to meet both requirements within the framework of academic teaching and further education, a novel training concept was developed and utilized at wbk’s practical and engineering-oriented Learning Factory on Global Production (LGP). The concept aims promoting professional and methodological competencies. Based on specified teaching and learning objectives, indicators are defined to make the promotion of these competencies ascertainable.

Sustainability of production and supply chains can be achieved by efficient planning. However, customers’ demand for multi-variant products and short lead times poses a challenge for automobile manufacturers not receiving customer orders in the mid-term planning horizon. To meet this uncertainty, this paper shall introduce an approach for anticipating customer orders by generating planned orders and for matching planned orders with incoming customer orders. Planned orders enable the integration of sales planning, production planning and material requirements planning in the mid-term and short-term planning horizons. In conclusion, resources can be used more efficiently to fulfill customer needs.

Companies operating assembly systems in global production networks constantly have to deal with change drivers. For the design of adaptable assembly systems, change drivers can be considered as fluctuating KPIs, such as labor costs, as well as changing KPI targets, such as rising quality requirements. In this paper, a concept for the design of changeable assembly lines with scalable automation is introduced and applied to the Learning Factory Global Production at KIT. The change of the automation level over time is based on an ex ante evaluation and ex post performance assessment of the impact of change drivers.

Rotor and stator stacks consist of laminated electrical steel sheets and represent the essential components of an electric drive. The process chain for the production of laminated stacks comprises two core steps: first, the separation of the final contour of the electrical sheets and second, the joining of individual sheets to a laminated stack. Both steps can be executed by different technologies. In this contribution, the influence of the separation technologies stamping and laser cutting on material properties of the individual sheets were investigated. In addition, different joining possibilities for stacking of the electrical sheets were also part of the study. Here, gluing, interlocking, baked varnish joining and laser welding were considered. For the laminated stack, a single tooth geometry was chosen, which was produced in three different lengths. In addition, a wide variety of sheet material was used - given a range of material thicknesses between 0.1 and 0.35 mm. Sheets and single teeth were measured with respect to their mechanical, geometrical and electro-magnetic properties, respectively. The measurements of the sheets, for instance, comprised burr height, contour and microhardness. In all stamped materials a significant increase in microhardness could be seen at the stamped edge. The geometrical properties of the laminated stack, namely dimensions, form and orientation are relevant for the assembly of the electric drive and were measured with tactile coordinate metrology. These measurements showed that gluing as well as stamping lead to an increase of manufacturing variances with increasing length of the laminated stacks. On the other hand, baked varnish stacking showed very stable results with low deviations. Laser welding showed good results as well in the geometric measurements. Depending on the application, laser welding can thus be seen as future alternative to common stacking technologies. The measurement of the electro-magnetic properties revealed a higher increase in power loss on stacks produced from laser cut sheets than on those made from stamped material. This difference was visible only on measurements of stacked sheets such as laminated ring cores or single teeth. Non-laminated sheets measured at the Epstein frame showed no difference in deterioration of the electro-magnetic properties between both separation technologies.

Selective Laser Melting (SLM) offers great potential for a cost-effective response to individualized customer requirements as well as the realization of a lightweight design due to SLM's tool-free design. Yet, one of the main barriers for the use of this technology in a series production environment is the high production cost. Existing approaches to reduce production costs have only been focusing on increasing the build-up speed of the additive manufacturing process. To enable SLM for series production it is essential that the whole production chain including the design of the SLM system will be optimized. In this paper, a simulation model is developed that aims to evaluate the cost efficiency of SLM process chains including all pre- and post-processing step. The implemented cost model allows for the identification of the main levers to optimize the system configuration and consequently the development and evaluation of new concepts for SLM machines. Preliminary results indicate that modular concepts realize a higher throughput, a better utilization of resources and therefore lower costs compared to integrated SLM machine concepts. Furthermore, the results point to the challenge of a smooth production in case of builds consisting of a high number of small parts.

The overall market trend depicts an increasing demand for electric or hybrid vehicles. This demand cannot be predicted precisely because of volatile influencing factors. Automotive companies are therefore confronted with the challenge of rapidly adapting their production systems accordingly. An approach to handle the variety of models within final assembly is to establish mixed model assembly lines. The subsequent integration of vehicles using alternative propulsion concepts into single model assembly lines stands as a great challenge in final assembly. Within this paper, an approach for the greenfield planning of assembly lines using the concept of changeability is presented. The approach focusses on the integration of a new propulsion concept in an existing assembly line. Hereto, the line allocation problem is solved for a fixed production volume ratio using an optimization algorithm. Thereafter, the production volume ratios are varied in order to identify an optimal solution for line balancing and assembly equipment.

To further improve the power density of modern electric drive technologies many motor designers decide to increase the rotational speed of the motor up to several tens of thousands revolutions per minute. Along with these high frequencies of the fundamental wave of the flux density inside the laminated stator cores, the electromagnetic strain of the core and the importance of the iron losses are increasing. Due to this, the high amount of different mechanisms, responsible for these iron losses, need to be identified and associated to the appropriate production process. For this reason, a suitable and inline-capable electromagnetic measuring method is used to determine the iron losses for real motor stator core geometries and to separate the impact of different production steps. In this paper, the large number of manufacturing methods for stator cores is presented and the iron losses are assigned to the corresponding production step in an overall consideration. The cause of the measured losses are identified and described. The mentioned measuring adapter can also be used to monitor a specific assembly line with regard to separation and joining quality to represent an innovative and economic possibility of quality assurance

In the context of an increased globalisation of sales and procurement markets companies are distributing their manufacturing activities in global networks. A key challenge is to ensure the overall production quality despite distributed value creation processes in complex manufacturing networks. Hence, a simulation model is presented, which allows for an evaluation of quality control strategies in global manufacturing networks. Based on the approach of Value Stream Mapping (VSM), which is enhanced by quality-relevant elements, a simulation approach is developed to dynamically evaluate different quality control strategies taking the individual target systems and site roles of the involved partners in the manufacturing network into account.

Modern globalization is characterized by a production in networks. With an increasingly dynamic business environment, the focus of production planning shifts to network management. This paper presents a method for managing production networks. The emphasis is on capacity planning and the use of instruments that render the staff more flexible. The methodology also integrates an approach to hedge against the risk of systematic errors in forecasting the market demand.

Growing requirements of Sheet Molding Compound (SMC) parts make new material combinations necessary. One strategy is to reinforce SMC with unidirectional carbon fiber tapes to improve its mechanical properties. As quality assessment of cured parts is necessary, examination of semi-finished materials would be favorable. Two types of nondestructive testing methods, Thermography and Ultrasound, are compared to determine the best control method. These methods are examined on cured plates and semi-finished material to identify defects like air inclusions, delamination, misaligned fibers and microstructural changes. The focus of this paper is an assessment of the testing methods for the manufacturing process.

In the last years, x-ray computed tomography (CT) has gained more and more importance in metrology. However, computed tomography is a complex and indirect measurement procedure. Many factors contribute to the measurement result, which makes it difficult for the user to relate cause and effect. For example, the user-set scan parameters significantly influence the measurement result. However, the selection of scan parameters is still based on the experience of the CT user, while the influence of the parameter choice on the measurement result cannot be quantified. This leads to diverging and non-optimal scan results. The quality of the CT scan can only be evaluated afterwards, e.g. by visual inspection of the reconstructed volume. Taking into account that the process chain of CT measurements is highly complex, the very first step is the generation of reliable high quality projections that can then be fed into the reconstruction. The quality of these projections can be described quantitatively by image quality measures. Thus, in this paper, an approach regarding projection based evaluation of CT image quality in micro computed tomography is presented. By performing a set of experiments, the influence of projection image quality on the reconstructed volume and respectively on the measurement result is evaluated. A derived model relates the projection quality measures to the actual measurement error of the CT scan. Hence, the proposed approach defines a reliable, combined quality measure, which is based on a small number of projections acquired before the actual scan. An algorithm evaluates the quality of those projection for every workpiece that has to be measured. Based on the evaluation, it varies the scan parameters, until an optimal projection quality is reached and a reduced measurement error in the CT scan is achieved.

X-ray computed tomography (CT) is a promising technology for quality assurance of industrial parts. However, computed tomography for dimensional metrology is a complex and indirect measurement procedure, whose results depend on a variety of influencing factors. To ensure that a measurement is traceable back to the basic SI units, a statement about the measurement uncertainty has to be given together with the actual measurement result. A generally accepted method for uncertainty evaluation is the use of calibrated workpieces. However, the influencing factors throughout the measurement procedure that contribute to the uncertainty are not quantified individually and remain unknown. The quality and reliability of the measurement, expressed in measurement uncertainty, hereby depends on hard- and software as well as user-set scan parameters. Not only scan parameters, such as current, tube voltage or exposure time, can influence the measurement results, but also surface determination and geometrical evaluation of the measured features add to the measurement uncertainty. In this contribution, the measurement procedure for metrological computed tomography is assessed and influencing factors throughout the different steps in the measurement procedure are identified as well as quantified. The approach is used to analyze the data quality of different measurements with a test object. The CT data are compared to tactile calibration data of the object and an experimental uncertainty evaluation is given.

Die Röntgen-Computertomographie gewinnt in der industriellen Messtechnik immer mehr an Bedeutung. Allerdings sind das Messergebnis und die dazugehörige Messabweichung stark von der Wahl der Aufnahmeparameter abhängig, die durch den Anwender getroffen wird. Daher wird eine Methodik vorgestellt, die eine automatisierte Einstellung der Aufnahmeparameter mit dem Ziel einer jeweils verringerten Messabweichung ermöglicht. Mithilfe von Bildqualitätsparametern kann die Bildqualität von Einzelprojektionen bewertet und diese im Rahmen eines experimentellen Modells mit der merkmalspezifischen Messabweichung der Einzelmessung am rekonstruierten 3D-Volumen verknüpft werden. Aus dem Modell kann dann die optimale Bildqualität der Einzelprojektionen abgeleitet werden, auf deren Basis dann automatisiert und messaufgabenspezifisch ein bauteil- und geräteabhängiges Set an optimalen Aufnahmeparametern bestimmt wird. Die hierfür notwendige Beurteilung der Bildqualität von Einzelprojektionen kann nur mit objektiven Kennwerten erfolgen. Im Beitrag werden daher verschiedene Kenngrößen zur Bewertung der Bildqualität vorgestellt und auf ihre Anwendbarkeit in der Computertomographie überprüft.

Globalization, growing environmental awareness as well as rising and volatile resource prices contribute to an increasingly uncertain Business environment in manufacturing. It is impossible to consider all future developments of external influences when planning and setting up a new manufacturing system. Therefore, companies must react with constant change and readjustment. This paper presents an approach based on simulation and design of experiments for the identification of suitable improvement strategies that counteract negative effects of external change drivers in discrete manufacturing systems. It covers selection of an effective strategy under consideration of its impacts. Thereupon, the ideal intervention threshold for the implementation of the selected strategy is derived. The methodology is applied to an ideal typical production line.

The current production environment is characterized by increasing dynamics. Given these volatile production conditions, robustness becomes an ever more important characteristic for production systems. The robustness shall ensure successful production in a varying production environment. Robustness therefore is a compromise between stable and efficient production systems. The concept of robustness as a characteristic of production systems will be regarded in this paper. Besides the pure concept, the entities influencing robustness will be analyzed. The main factors herein are the regarded system parameters, the regarded time-frame and the range of disturbances. These factors strongly affect the performance of a production system. For a proper analysis of a production system’s robustness, the given factors need to be specified. Therefor a general framework of robustness will be presented in the paper. The regarded robustness can be classified using the framework. Given this prerequisite, the robustness can be analyzed regarding the performance behavior a production system exposed to a dynamic environment. The performance behavior will lead to possible measures for production system robustness.

For calibration and performance assessment of industrial CT devices, reference objects can be used. This paper presents three unique test bodies comprising of distinctive geometric characteristics and traits resembling those that are often exhibited by real industrial components. The framework for the conception and development process of these objects is based on a systematic approach to ascertain the geometry, dimensions and suitable materials for the final test bodies. The specimens are designed to cover all common geometric tolerances in addition to dimensional measures. Moreover, the distinctive properties and features exhibited by each of the three designs, along with an allowance for a comprehensive geometric dimensioning and tolerancing (GD&T) analysis, challenge different aspects of the CT process. To ensure traceability, the test bodies are calibrated with high accuracy micro coordinate metrology. Therefore, a data evaluation strategy is discussed, which allows the comparison of data points from the tactile measurement to the extracted surface of the CT measurement.

Modern globalization leads companies into a changing environment with a highly uncertain future development of key drivers of change. Especially, global production networks are affected by uncertainty and dynamic changes. Reactiveness becomes of crucial importance, as the adaptation to environmental conditions is the key to maintain competitive advantages. This article presents an approach for flexible migration planning in global production networks. The focus is on the formulation of a Markovian Decision Process (MDP) that enables the identification of optimal reactions to stochastic changes of key drivers of change. The formulation includes the description of a multi-level modelling approach for global production networks. Furthermore the valuation model of the reward function of the MDP is discussed in detail. Finally, the paper provides a brief description of exemplary optimization results solving the MDP by backward induction.

Due to shorter product-life-cycles, innovations in production engineering have to keep pace with today's technologies. As a result, factory planning is more and more challenged by technologies being immature for series production. Usually, these immature technologies place special demands on production layout and quality management, for example. These demands have to be considered in the factory planning process. Moreover, technologies are part of the production process that is created by a series of technologies. Hence, a planning process has to ensure that the positive aspects of a new technology are not negated by arrangements to protect the technology chain against failure due to immature technologies. With Selective Laser Melting (SLM) used as example for an additive manufacturing technology, this paper presents a method of planning a production system by taking the technology maturity into account. Possible requirements of an immature technology interacting with the process chain will be addressed as well as adjustments to be made to the factory planning process.

The increasing globalization forces manufacturing companies to organize their production in global networks, which include company internal sites as well as locations of external partners and suppliers. Each site in this network has an assigned strategic role according to the specific location factors, i.e. qualification level of employees or available process technology, and the defined specialization of each site, i.e. regarding served market, final product or realized processes. This role defines an individual target system that considers at least the dimensions cost, quality and time. Each site acts autonomously according to the target system. Since it is crucial for the success of the company to ensure the demanded quality of the final product with minimal cumulated quality costs and lead times, the quality control strategy for the production network has to be designed according to the target systems of the individual sites. The presented article describes an approach, which enables globally operating companies to efficiently plan their efforts for their quality control measures in their respective production network taking the specific site roles into account. In a first step, a value-stream-based methodology is presented, which visualizes quality characteristics as well as related quality inspections in the production process chain and which identifies potentials in the quality control strategy across locations. In a second step a simulation approach is used to evaluate the effects of different quality measures considering dynamic influencing factors and individual target systems, so that the optimal quality control strategy for the production network can be identified.

Given today’s demand for product variants in different market segments, manufacturing companies are facing high degrees of complexity when utilising existing global manufacturing networks. To remain competitive, reallocating production of product variants according to their lifecycle becomes essential in order to use resource capacities more efficiently. Therefore, companies must take into account costs and benefits of standardisation and specialisation of their production facilities to meet long-term corporate goals. An approach for allocating products to plants is sought that addresses the stated matters by allowing for reconfiguration of production networks, determining optimal flexibility levels of production facilities, and taking strategic guidelines into account. In this paper, a resource-based approach is introduced in which product variants and production resources are mapped to production processes in order to determine optimal configurations of the manufacturing network while considering restrictions. The approach will be applied to the final assembly of a large scale products’ manufacturer.

Increasing globalization drives companies to produce in global networks, where each site acts autonomously according to its individual target system, influenced by specific location factors or its defined specialization. Despite distributed value creation processes, the overall production quality must be ensured. Hence, a simulation-based approach is presented, which allows for designing an optimal across-site quality control strategy by evaluating different quality measures depending on individual target systems of different sites. At first, a categorization of quality measures and an applicable target system model are presented. Secondly, a simulation approach is described to evaluate implemented measures according to defined performance indicators.

Build-to-order series production is gaining increasing importance as markets demand customer-specific product variants. Orders have to be assigned to plants and periods in global production networks and then to lines and cycles. Consequently, respective workloads as well as supplied materials have to be balanced due to limitations in resource capacities. As first step planning defines the solution space for second step planning, this paper introduces a mathematical model for order assignments to plants and periods anticipating assignments to lines and cycles. Given that orders are not fully specified for first step planning, the approach includes provisions for dealing with uncertainty.

Frugal innovation theory is proposed to help companies rethinking their current product design and production strategies facing competitive challenges. Co-evolution of product and production systems is required to reach frugality goals. The success of the co-evolution strategy should be based on robust models ensuring the global consistency of the whole development process. Modular-based models are a good solution for such problematics since they provide a common semantic for the representation of the physical product structure as well as the organizational structure of the production system through the definition of interfaces between elements and the hierarchical decomposition of a system into different elements. This paper proposes a conceptual modular-based approach dealing with the selection of product modules influencing the selection of suppliers and the allocation of orders in a global production network. The indirect linking of the customer to production is also discussed in terms of the timewise restrictions in selecting product modules offering the customer a maximum degree of flexibility in product specification.

For efficient, effective and economical production operation management in a manufacturing unit of an organization, it is essential to integrate the production planning and control system into an enterprise resource planning. Today’s planning systems suffer from a low range in planning data which results in unrealistic delivery times. One of the root causes is that production is influenced by uncertainties such as machine breakdowns, quality issues and the scheduling principle. Hence, it is necessary to model and simulate production planning and controls (PPC) with information dynamics in order to analyze the risks that are caused by multiple uncertainties. In this context, a new approach to simulate PPC systems is exposed in this paper, which aims at visualizing the production process and comparing key performance indicators (KPIs) as well as optimizing PPC parameters under different uncertainties in order to deal with potential risk consuming time and effort. Firstly, a production system simulation is created to quickly obtain different KPIs (e.g. on time delivery rate, quality, cost, machine utilization, WIP) under different uncertainties, which can be flexibly set by users. Secondly, an optimization experiment is conducted to optimize the parameters of PPC with regard to the different KPIs. An industrial case study is used to demonstrate the applicability and the validity of the proposed approach.

Nowadays, micro motors are used in combination with micro transmissions in manifold industrial applications such as dental drills or the equipment for minimally invasive surgery. Micro transmissions consist of micro gears, which are critical to their functionality. To ensure proper operation of the micro gears for their expected purpose, a reliable prediction of their lifetime is crucial. Lifetime evaluation is particularly important for micro gears, as the influence of their geometric shape deviations on their load rating is significantly higher in comparison to gears with larger modules. In this article, a methodology is introduced to enable a quality dependent lifetime prognosis of micro gears. For this, micro gears are systematically operated by means of a highly precise experimental setup, until a defect of one of the gears can be detected. The characteristic loads at the tooth flanks during the experiments can be determined by means of finite element analysis based on CAD models of the real gear geometry of the specimen determined by accompanying 3D CMM measurements. These data can be statistically evaluated

Rotor and stator stacks consist of laminated electrical steel sheets and represent the essential core components of an electric drive. These sheets are frequently made of nongrain- oriented electrical steel, fully finished, and produced by means of stamping. A cost efficient production requires prolonging tool life by reducing tool wear. Hence, the presented work aims at analyzing wear behavior of stamping tools in the process of stamping electrical steel sheets with baked varnish insulating coating. Based on stamping tests, a series of long-term experiments with initially sharp cutting elements made of hardened tool steel was conducted over a period of several hundred thousand punching strokes. The number of strokes was analyzed with regard to its effects upon defined abrasion parameters at the cutting edges as well as upon burr and cut surface at the produced electrical sheet.

Rotor and stator stacks consist of laminated electrical steel sheets and represent the essential core components of an electric drive. These sheets are frequently made of non-grain-oriented electrical steel, fully finished, and produced by means of stamping. A cost efficient production requires prolonging tool life by reducing tool wear. Hence, the presented work aims at analyzing wear behavior of stamping tools in the process of stamping electrical steel sheets with baked varnish insulating coating. Based on stamping tests, a series of long-term experiments with initially sharp cutting elements made of hardened tool steel was conducted over a period of several hundred thousand punching strokes. The number of strokes was analyzed with regard to its effects upon defined abrasion parameters at the cutting edges as well as upon burr and cut surface at the produced electrical sheet.

Durch Industrie 4.0 lässt sich sowohl der Trend der individualisierten Produktdefinition, als auch der der echtzeitfähigen Produktionssteuerung realisieren. Sie ist ein nicht mehr aufzuhaltender Megatrend mit Elementen, deren Chancen und Risiken jedoch noch nicht voll umfänglich verstanden sind. Wesentliche Enabler sind dabei kostengünstige Sensorik sowie die Verfügbarkeit aller relevanten Informationen in Echtzeit durch Vernetzung der Akteure. Hinsichtlich standortübergreifender Prozesse bietet Industrie 4.0 durch die digitale Vernetzung eine vielversprechende Ausgangslage, um das Auftragsmanagement und die Steuerung globaler Produktionsnetzwerke und Supply Chains maßgeblich zu verbessern. Faktoren wie eine sichere Kommunikation und die Beibehaltung der Datensouveränität stellen hingegen Herausforderungen dar, die im Rahmen der Industrie 4.0 gelöst werden müssen, um langfristige Akzeptanz zu erreichen. Standardisierungsmaßnahmen müssen getroffen werden, die nicht nur den Ablauf von Informationserfassungs- und Auswerteprozessen betreffen, sondern ebenso den Umgang mit sicherheitstechnischen Fragestellungen. Ziele, die sich für den Produktionsstandort Deutschland daraus ergeben, sind der Erhalt der Vorreiterstellung in der Bruttowertschöpfung, sowie der Ausbau eines signifikanten Marktanteils in Bezug auf Lösungen der Industrie 4.0.

To remain competitive in an environment of emerging markets and increasing globalization, many companies in the manufacturing industry are facing challenges. Adding new production capacities or adapting existing production capacities of their manufacturing network becomes necessary to realize local production advantages and for serving new markets. In this regard, network configuration alternatives need to be evaluated according to the decision maker’s perspective. Thereby, the goal-orientation of each perspective has a fundamental influence on the design of manufacturing sites and their connections. The objective of this paper is to demonstrate the influence of different perspectives on design decisions of manufacturing net-works. Therefore, seven relevant perspectives are identified based on current trends in literature. In addition, more than 70 key performance indicators (KPIs) were identified and assigned to the different perspectives. Based on the reference point method and the analytical hierarchy process, a comprehensive approach is developed enabling the evaluation of manu-facturing network alternatives according to different perspectives and related KPIs. The KPI-based approach allows for adjustment to manufacturing network and target system specifics using weightings on perspective level and KPI level. The paper is concluded by demonstrating the functionality of the approach using an example.

Based on the fundamental principle of teaching psychology that retentiveness increases if students actively apply learning topics rather than only attend oral or visual presentations, the concept of learning factories becomes more and more popular. Academic education in the field of production science is imparted by means of real-world manufacturing facilities. By applying the manufacturing process of a real product, students or professionals incorporate the learning contents effectively and gain consciousness about their practical implications. Most learning factories are focused on lean manufacturing, lean administration or resource efficiency. As today manufacturing is not only subject to a single factory, but a network of globally distributed production sites, at the wbk Institute of Production Science, currently, a learning factory dealing with the topic of global production is developed. On the one hand, the curriculum of the Learning Factory Global Production (LGP) involves the specifics of local production sites with different location factors, such as different degrees of automation, cost structures and qualification levels, and their effects on the reconfigurability of the production systems. On the other hand, the interaction of the production sites in a globally distributed production network and the strategic configuration of the network are also subject to the curriculum. The manufacturing processes are exemplified by the assembly of an automotive e-motor with transmission in the learning factory on global production. The learning factory is realized in cooperation with the Robert Bosch GmbH.

Industrial computed tomography is getting more and more important in dimensional metrology. However, in most cases the selection of scan parameters is based on the experience of the CT user, while the influence of the parameter choice on the measurement result cannot be quantified. This leads to diverging and non-optimal scan results. The quality of the CT scan can only be evaluated afterwards, e.g. by visual inspection of the reconstructed volume. In this paper, an approach regarding projection based evaluation of CT image quality is presented. Different projection based quality measure are assessed, which enable the evaluation of the image quality before the actual measurement procedure is completed, such that the expected image quality of the scan can be pre-estimated. By means of the new method, adequate scanning parameters for each measuring task can be chosen beforehand, which can lead to a reduction of the measurement error.

Nowadays, micro motors are used in combination with micro transmissions in manifold industrial applications such as dental drills or the equipment for minimally invasive surgery in the medical industry, hexapod micro positioning systems for wafer processing in the field of industrial automation or adjustable automotive components such as fixings of LCD monitors. Micro transmissions consist of micro gears, which are critical to their functionality. Micro gears are typically defined as gears with a module which is lower than 200 μm. To ensure proper operation of the micro gears for their expected purpose, a reliable prediction of their lifetime is crucial. Lifetime evaluation is particularly important for micro gears, as the influence of their geometric shape deviations on their load rating is significantly higher in comparison to gears with larger modules. This is a consequence of the larger shape deviations of micro gears in relation to their part size due to their manufacturing processes. The lifetime of micro gears can be evaluated by an experimental approach. Within this a pair of micro gears is systematically worn under realistic, clearly defined conditions, until a defect of one of the micro gears can be detected. This can be conducted by means of a highly precise experimental setup. In this article, a methodology to calculate the characteristic loads at the tooth flanks of the pair of micro gears during the experiments based on finite element analysis is introduced. For this purpose, CAD models of the real gear geometry of the specimen are deducted by means of high precision 3D measurements and spline interpolation. On the basis of these data, the lifetime of the micro gears dependent on their shape deviations can be predicted by means of a model based on reliability statistics.

The material group of carbon fiber reinforced polymers (CFRP) is getting more important as a construction material. Due to its high mechanical load capacity CFRP can be applied in many applications. The low density in combination with its mechanical properties makes this material predestinated for lightweight design. Due to this CFRP are getting into the focus for the automotive serial production. But to establish them the production costs and the cycle times have to decrease significant (McKinsey & Company 2012). To facilitate a large-scale use the automated production has to be further developed. Irrespective to the kind of infiltration the forming operation of the semi-finished textiles is a significant process step that has to be controlled. In the so called preforming process the two dimensional semi-finished textiles are laid up in several layers and are transformed into a three dimensional near net shape geometry. Due to the anisotropic properties of carbon fibers this process is crucial for the final mechanical properties of the consolidated part. The complexity of the process makes it susceptible to defects such as form deviations, folds and misalignment of the textiles (Härtel & MIddendorf 2013). These deviations can lead to a significant loss of the mechanical properties of the final part. Currently these kinds of defects are typically detected in an end of line quality inspection by using nondestructive testing (NDT) methods. Thus to get a holistic understanding of the production process it is necessary to measure the preform directly after the preforming process (Lanza & Brabandt 2013). The objective of the presented approach is to generate a complete surface measurement of the preform. Therefor a triangulation system using laser stripe sensors is implemented on a three-axis-kinematics that moves the sensors over the surface. It will be discussed what kind of specific challenges occur by measuring carbon fiber preforms and how they are solved by the presented setup. As a reference carbon fiber specimens representing typical geometric features are investigated. Based on the generated data-sets which are represented by a cloud of points further analysis can be performed. The data can help to improve the manufacturing technologies within the preforming process by getting a three dimensional model of the preform. This model offers the opportunity to analyze the macroscopic behavior of the semi-finished textile in the forming operation. Furthermore the three dimensional model of the preform can be used as a validation for draping simulations. In a direct link to the production process the implementation of an inline metrology system will give the possibility to evaluate deviations from given tolerance limits so that a quality judgment can be made at an early stage. This leads to reduced production costs and scrap rates. The presented metrology system will also give an support to set the right tolerance limits. By digitalizing specimens with known defects a holistic approach for the evaluation of effects of defects (EoD) will be possible by giving essential information to combine them with NTD and destructive end of line tests.

Nowadays, micro transmissions are used in combination with micro motors in manifold industrial applications, e.g. in the medical industry in actively controlled prostheses. Micro transmissions consist of micro gears with a module < 200 μm. The main function of micro gears is a proper operation over the required lifetime. Lifetime evaluation is particularly important for micro gears, as the influence of geometric shape deviations is very large. Efficient production metrology is based on function-oriented measurements. Thus, in this article, a methodology is introduced to enable a function-oriented evaluation of micro gear measurements. For this purpose, high-precision 3D CMM measuring data are processed by finite element method (FEM) simulation to calculate the characteristic loads. These are correlated with experimental data of lifetime experiments.

The increase of resource (energy and material) efficiency by eliminating unnecessary consumption represents the logical continuation from lean manufacturing to lean and green manufacturing. However, economic efficiency remains the primary decision criterion for the implementation of corresponding strategies. This paper presents a simulation based approach for monetary assessment of lean and green manufacturing systems considering non-monetary green limits. Inclusion of material and energy consumption as well as resulting greenhouse gas emissions enables planners to predict the overall economic performance of a factory. Furthermore, product variant specific footprints of material and energy demands as well as resulting emissions support in-depth analysis of value streams in manufacturing.

Mikrogetriebe kommen heute in Kombination mit Mikromotoren in vielfältigen industriellen Anwendungen zum Einsatz. Beispiele stellen Dentalbohrer oder Ausrüstung für die mini-mal-invasive Chirurgie in der Medizintechnik, Hexapod-Mikropositionierungssysteme zur Waferbearbeitung im Bereich der industriellen Automatisierung oder verstellbare Automo-bilkomponenten wie Befestigungen von LCD-Monitoren dar. Mikrogetriebe bestehen aus Mikrozahnrädern mit einem Modul < 200 μm, die entscheidenden Einfluss auf die Funkti-onserfüllung der Getriebe haben. Um den gewünschten Betrieb der Mikrozahnräder zu gewährleisten, ist eine zuverlässige Vorhersage von deren Lebensdauer entscheidend. Bestehende Normen werden den Be-sonderheiten von Mikrozahnrädern hierfür jedoch nicht gerecht. Insbesondere weisen Mik-rozahnräder im Verhältnis zur Bauteilgröße deutlich höhere Fertigungsabweichungen auf, sodass ein größerer Einfluss dieses Einflussfaktors auf die Tragfähigkeit zu erwarten ist als bei Makrozahnrädern. In diesem Beitrag wird ein neuartiger Ansatz präsentiert, mit dem die Lebensdauer von Mik-rozahnrädern unter Berücksichtigung der Fertigungsabweichungen auf Basis von Lebens-dauerversuchen bewertet werden kann. Hierzu werden Zahnradpaarungen systematisch unter realitätsnahen, klar definierten Bedingungen ermüdet, bis ein Defekt an einem der Mikrozahnräder auftritt. Dies kann mit Hilfe einer hochpräzisen experimentellen Messan-ordnung durchgeführt werden. Vor und an definierten Zeitpunkten während der Versuchs-durchführung wird die 3D-Geometrie der Mikrozahnräder mittels eines hochgenauen Mikro-Koordinatenmessgeräts vollflächig gemessen. Auf Basis der geometrischen Messdaten werden FEM-Analysen der Zahnräder durchgeführt, um die charakteristischen Belastungen an den Zahnflanken zu berechnen. Aus den experimentellen Daten kann schließlich ein Modell zur Lebensdauerprognose unter Berücksichtigung der Ausfallwahrscheinlichkeit abgeleitet werden.

Electric mobility seems to be a viable solution for individual mobility in future. However, the use of these alternative drives is accompanied by high costs caused by the battery production. One approach to reduce the production costs is to reduce the rejection rate by integrating appropriate quality assurance measurements in assembly systems. To avoid subsequent, epensive modifications, those measurements must be integrated into the assembly system planning. Therefore, possible integrated measurement technologies for quality-critical characteristics have to be developed and evaluated for the use in the battery assembly. The results are integrated in a planning system to support assembly planners.

A critical part in the process chain of manufacturing electric drives is the production of laminated stacks. Due to their excellent isolating characteristics, electrical sheets that are coated with baked varnish are often considered to be electric benchmarks. Besides a pure loss evaluation of the laminated stacks, a cost reduction of the overall system should also be aimed for. This paper deals with the optimization of a real production line and focuses on the process chain: stamping with subsequent baking of single-tooth stator stacks for automotive application. The main focus of the improvement potential lies on the baking process, including the necessary pre- and post-processing. In order to optimize the existing line, the simulation software Tecnomatix Plant Simulation was used. Through bottleneck analyses of the modeled system, targeted improvements were derived to achieve a significant increase of the output. Those simulation studies enable virtual adjustments to the running system and a quantification of the expected effects. In the context of a real example, quantitative improvement potentials are presented and the limitations of the process chain baked varnish stacking are shown.

Robustness becomes a crucial feature of production systems. On the one hand, the systems are subject to many disturbances and on the other hand, a reliable production is demanded. A robust system shall be able to keep the working process on a good performance level despite occurring disturbances. To enable such a system’s behaviour, different actions have to be taken. The paper presents an approach to identify the best action to improve a system’s robustness on an operational and tactical level by investigating its disturbances and performance.

An increasing and volatile demand in emerging economies challenges manufacturing companies to decide, whether the new markets can be satisfied with the existing product portfolio, or to which extent it has to be adapted to meet the regional market requirements. A three-step approach to enable globally operating companies to efficiently deliver innovative products adapted to regional requirements regarding product design and functionality is presented. In the first step a bottom-up process is formulated on how to design customer-oriented products for frugal innovation integrating the customer directly in the design process. In the second step a methodology to design production systems in accordance with the customised products including the customer in the order-fulfilment process is composed, while in the third step a multi-objective optimization approach is developed to strategically design production networks and to plan and control the designed networks on an operative level taking dynamic business environments into account.

Robustness becomes a crucial feature of production systems. On the one hand, the systems are subject to many disturbances and on the other hand, a reliable production is demanded. A robust system shall be able to keep the working process on a good performance level despite occurring disturbances. To enable such a system’s behaviour, different actions have to be taken. The paper presents an approach to identify the best action to improve a system’s robustness on an operational and tactical level by investigating its disturbances and performance.

Mass reduction of vehicles is getting increasingly important in the automotive industry. Because of their low weight, especially lightweight structures made of Carbon Fiber Reinforced Plastics (CFRP) can be seen as a key element to achieve the climate targets of cars in the future. Current especially complex shaped geometries are challenging for the serial production of CFRP. To enable the processes and to reduce scrap rates in the production process, a reliable metrology system has to be established in the early stage of preforming. In the preforming process quality critical features such as the final geometry are defined. Previous tests have shown that laser stripe sensors offer a high potential to measure the surface of the preforms. Nevertheless there are still challenges that will be focused by the presented approach. Due to complex 3D geometries, a combination of two laser stripe sensors has to be used to achieve an area-wide scan by reducing shadowing effects. Because of the limited depth of focus, the two laser stripe senor systems have to be tracked over the geometry equidistant. Furthermore, the sensor system has to be moved in a scanning mode over the preform in several paths to evaluate the whole geometry. To generate a basis for a measurement data evaluation, the scans have to be manipulated and processed in several steps. First, a z-value correction has to be made because of the equidistant scanning. Second, a data fusion of the two laser stripe sensors to one cloud of points representing one scanned path has to be performed. Third, the different scanning paths have to be matched to one complete cloud of points. This finally can be used for further data-processing steps such as a nominal-actual comparison.

Owing to the high flexibility when using a laser beam as a tool, its field of applicationgrows more and more. In case of micro structuring of metal components especially the use of ultra short laser pulses offers a high potential for precise and high Quality results. However the economical application in an industrial surrounding is still affected by different issues, e. g. a lack of process efficiency. In this work, different factors and their influence on the ablation process are investigated for a improvement of the process efficiency for structuring micro-sized dimple structures on big metallic surfaces. To achieve this goal the repetition rate and the pulse strategy of the laser have to be in focus. Furthermore the interaction between consecutively produced holes and the heat accumulation for each hole were particularly taken into consideration. To constantly ensure the capability of the ablation process it is essential to measure and analyse the results of the process. This sets up the focus on a fast and reliable quality assurance of the ablated microstructures. Therefore this paper covers an automated evaluation approach for optical measurement data of microstructured surfaces in addition to the manufacturing approach.

Micro transmissions are very important systems in manifold applications, e.g. in the medical or automotive industry, which enable movements at very small available space. Micro gears are crucial parts of these transmissions. At the Karlsruhe Institute of Technology a methodology for their lifetime prediction is to be developed, which specifically integrates the measured shape deviations of the micro gears. This article outlines how the influence of the shape deviations of the micro gears on their reliability can be modelled by means of the finite element method (FEM).

Companies in the manufacturing industry today are faced with increasing challenges with respect to cost effectiveness, lead time and quality of the production system. Dealing with these contradictory goals, an important task is the selection of suitable solutions for the integration of inspection processes within the process chain, which are necessary to ensure the required production quality. For this, supportive and easily applicable planning techniques are required to analyze and design the configuration of a respective process chain. Value Stream Mapping (VSM) is a state of the art tool which is very often used for this by professionals. It, however, is not capable of addressing the issue of a suitable integration of testing processes within the process chain. Yet, this provides valuable potential to facilitate the identification of effective testing equipment, testing strategies and quality control loops. Therefore, in this article an innovative approach called Quality Value Stream Mapping (QVSM) is presented. Based on the design elements of VSM, it provides a suitable tool for the visualization, analysis and design of quality assurance measures within process chains in manufacturing. The implementation of the developed approach is exemplarily shown for a complex value chain of a manufacturer in the electronic industry.

The use of sheet molding compounds (SMC) in diverse applications requires different specific material properties for each type of finished parts. These material properties have to be assured by a reliable quality control, which does not only have to be performed for the prefabricated SMC itself but also during the production process of the semi-finished material. This is of high importance because quality fluctuations and defects can already occur during the production of the semi-finished SMC. This results in high scrap rates as well as machine failure and can additionally cause further problems in the following process steps. Hence, an inline quality control can help to establish objective quality criteria for semi-finished SMC and can enable controlled and stable production processes. Therefore, this paper deals with quality assurance in the production process of semi-finished sheet molding compounds. Air entrapping and fiber distribution are identified as two parameters that influence the quality of the semi-finished product significantly. In addition, the early detection of a pending carrier foil failure can help to establish a stable process. The focus of this paper lies on how various, individually adapted metrology systems can be used for the detection of the respective characteristics and integrated into the production process of the semi-finished SMC. In particular, optical systems, such as area scan cameras and laser stripe sensors as well as thermographic sensors are discussed and possibilities for application-related sensor data evaluation are shown. This helps to reduce the scrap rates of parts and to establish a further automated production process.

Light-weight aluminium space frame structures are frequently used for small-volume products, such as sports cars. The assembly of these products has so far been mainly manual and requires the use of complex and expensive fixtures. To increase the profitability, the research conducted at wbk Institute of Production Science is aiming to achieve an automated, fixtureless assembly of such structures by the use of industrial robots. To achieve the required accuracies regarding the alignment of the joining partners, a new approach based on component-inherent markings has been developed. This article describes the approach for the fixtureless positioning of components and the validation of the marking detection.

In this paper an approach for a precise assembly of space-frame-structures is presented, while each of the single components features production-related deviations. The first section shows the results for the compensation of production-related deviations for dimensionally curved profiles in a space-frame-structure. The actual approach deals with the machining of the profile-end segments. Thus, the spatial alignment of the entire profile-contour can be optimized and therefore be adjusted to the theoretical profile-contour. In the second section, a flexible clamping-gripper for the assembly of space-frame-structures is presented. With this gripper, it is possible to handle and clamp different profiles for a certain assembly process.

In order to strengthen their position in the global market, firms in the plant engineering industry need to differentiate themselves from their competitors. The competition has led to diminishing margins for primary products and the realization that a successful product not only entails the efficient production of the primary product but also elements of the tertiary service sector. Particularly, the field of spare parts services and maintenance management present potentials for plant manufacturers.

This paper describes a systematic approach to increase the availability of production systems by an optimal maintenance and spare parts provision management, considering the realistic failure behavior of the regarded components and their operation conditions. The approach considers the component’s failure as the initial event of the planning and configuration process and emphasizes the integration of the effects of failure, especially in complex systems and production system chains.

Increasing competitive pressure in the production sector has led to considerable changes in the global competitive structure. Currently, companies attempt to counteract cost pressure by increasing their global outsourcing activities as well as focusing on their core competencies. Hence, global procurement has gained increasing importance among general purchasing activities of companies and is predicted to have an increasing influence on future cost development. Due to this development, companies are looking for new suppliers in low-wage countries. However, companies have to consider negative effects in the fields of quality, service level, and counterfeiting or plagiarising of merchandise. Therefore, cost savings in low-wage countries can only be achieved through major efforts during the planning and the realisation phase of the supplier selection process. Purchasing companies lack systematic assistance in analysing the procurement object and the economic environment of potential supplier candidates. This paper presents a two-step approach dealing with the issue of global procurement in low-wage countries and how this issue is faced taking business environment into account. In the first step, a method is described using the help of a requirement profile for suppliers and a cost structure analysis to select potential suppliers. In the second step, an approach for modelling and identifying potential dynamics and risks related to the acquisition of new suppliers in low-wage countries is developed.

This paper presents an approach towards an innovative and intelligent production control for a highly flexible and efficient production in an increasingly dynamic and complex environment. For this purpose, a novel and flexible production control is developed on the basis of intelligent rescheduling for global manufacturing networks gained by using of real-time information.

Mikrozahnräder sind wichtige Bauteile in vielfältigen innovativen Anwendungen. Die Computertomographie (CT) bietet aufgrund ihrer hohen Informationsdichte großes Potential für deren Qualitätssicherung. Der Artikel beschreibt eine Methode zur flächigen Messung von Mikrozahnrädern mit geringer Messunsicherheit, bei der die CT-Messdaten mit taktilen Messdaten fusioniert werden.

Micro gears are crucial components in micro trans-missions which are used in manifold industrial applications in e.g. medical, automotive, aerospace, industrial automation or robotics. Due to their small size and their important application purposes the requirements to their quality and reliability are typically very high. In this article the correlation between the manufacturing quality and the lifetime of micro gears is explored. The article presents a methodology to quantitatively describe the influence of geometric shape deviations and of the material structure of micro gears on their lifetime. A lifetime prediction model is described enabling the determination of the failure probability of micro gears with defined shape deviations and defined material defects dependent on the operating time and the present load torque. The model is developed by means of statistical reliability analysis methods on the basis of experimental data. The result of the model is a distribution of the failure probability for a specific gear type with known shape deviations and material defects to which a defined load is applied. The experimental data are determined via systematic abrasive experiments by means of an experimental rig, in each experiment rolling a pair of micro gears with a defined load until failure. Before each experiment and at suitable intermediate times the external shape as well as the internal material condi-tions of the micro gears are characterized non-destructively by means of coordinate metrology and computed tomography. The main benefit of the method is that a micro gear can be characterized already in the early development phase in a way such that its lifetime can be predicted within a small variance range. The knowledge of the expected lifetime dependent on the geometric shape and the material structure allows a more meaningful classification of micro gears. It provides important information for the design of micro gears in all of their various fields of application. For instance, by means of the new method the requested manufacturing tolerances of a micro gear can be determined in compliance with its required lifetime and the respective manufacturing processes and parameters can be adapted to this.

Electric vehicles are widely regarded as one solution of future mobility. However, they still pose multifarious challenges as the increase in demand for electric vehicles, the diversity of battery variants, the development of new battery designs and the alternative usable manufacturing technologies in the production process. Hence a battery assembly which enables its changeability and its reuse is required. Furthermore expensive raw materials, safety aspects and a so far not fully automated process chain require the integration of quality assurance aspects during assembly planning. Therefore product developers and machinery and plant engineers are supported in planning a quality ensured changeable and reusable - a so called multi-use - battery assembly. To this end, a configurator has to be developed to provide the planner a decision support. The configurator has to deduce from product-specifications single assembly stations for its battery assembly, evaluates them regarding their changeability and reuse as well as the OEE and costs of the entire assembly line and gives a prioritized list of assembly alternatives as the output.

The economic production of automotive electric drives challenges manufacturers and OEMs. In order to support the cost optimal technology choice, a real lamination stack production is assessed with respect to quantity and variant flexibility. Therefore the process chain of a sample product is analyzed from the coil material to the finished stack. The cost interdependencies are analytically modeled in order to calculate the production costs from a bottom-up perspective. The cost calculation is done for a punching as well as a laser-cutting line. Based on this evaluation manufacturing processes can be chosen and volume-flexible series production lines can be designed.

Global supply chains are subject to many disruptions of different kinds. In order to transform the existing rigid supply chains into shock-robust networks two dimensions have to be regarded: the supply chain dimension and the manufacturing dimension. On the supply chain dimension new product-service models are regarded which allow for a much higher service level and thus for a better resilience of the whole network. The manufacturing dimension enables these innovative product-service models by addressing the production processes of the individual player. Therefore an EU project has just started to conduct research on innovative decision-making methods which integrate production planning at single players into the management of the whole global network. Advanced tools will be implemented in a management cockpit at each player. CPS-data feed the cockpits and will give a clear view of the actual statues of the whole supply chain which drastically reduces complexity.

Energy and natural resource prices are subject to a rising tendency with increasing volatility worldwide. On account of growing demand and limited resources, companies are obliged to aim at minimum waste production. However, the forecast of effects of combined lean and green practices presents a major challenge. So far, they have predominantly been calculated, optimized, and assessed independently of one another. This paper introduces a methodology for a successive further development of lean and green production based on the proactive monetary assessment of combined effects of both lean and green strategies. The outlined approach covers data collection and evaluation of the current production system, calculation of relevant key figures of selected combinations of lean and green practices by use of a queuing theory based analytical material flow model, proactive monetary assessment of the analyzed combination, and deduction of a company-specific plan of measures.

Micro gears are crucial components in micro transmissions which are used in manifold industrial applications in e.g. medical, automotive, aerospace, industrial automation or robotics. Due to their small size and their important application purposes, their quality requirements are very high. Therefore, both precise measurement systems and sophisticated data evaluation techniques are required to characterize their quality sufficiently.
While measurements of gears were traditionally evaluated by means of line-based parameters according to DIN 3960/VDI 2607, some newer approaches propose methods for the areal characterization of gears. These provide the advantage of a higher accuracy of the measurement results due to the larger datasets of measurement points evaluated over the entire tooth flanks. Thus, an areal characterization is particularly suitable in the case of micro gears. Yet, this has not been analyzed, in particular, so far.
Most commonly, micro gears are measured by means of a micro CMM with a tactile sensor. However, in order to measure a sufficiently large number of data points for an areal characterization of the micro gears, a very long measurement time is required. A faster approach to measure a large amount of data points of a micro gear is provided by the application of computed tomography (CT). A set of several thousands of data points distributed over all flanks of the micro gear can be collected within few minutes. Yet, neither suitable measurement strategies for the CT characterization of micro gears have been investigated in detail, nor areal gear parameters have been determined based on CT measurements of micro gears so far.
Furthermore, while methods have been established to determine the measurement uncertainty for CMM measurements of micro gears, e.g. by means of an experimental approach using a capable reference standard, for micro gears no approach for the uncertainty evaluation of CT measurements has been investigated up to now.
Therefore, in this article, a general methodology is developed to measure micro gears by means of computed tomography, evaluate them based on suitable areal parameters and determine the measurement uncertainty by means of a reference standard. The methodology is validated by CT measurements of exemplary micro gears.

By focusing on core competencies and the utilization of international location advantages such as access to low-wage labor and local sales markets, global production networks are becoming increasingly complex. Additionally, turbulent times with great uncertainty forces globally acting enterprises to adapt their production networks. Therefore, it is crucial to determine the right point in time for change and also to identify the beneficial production network alternatives. In other words, globally acting enterprises have to answer the two questions of what to change and when to change. The presented method describes an approach for the strategic planning of global changeable production networks, based on future scenarios and a multi-objective optimization to identify the most favorable network configuration during the planning horizon. The multi-objective optimization is modeled as a mixed-integer MODM problem (multi- objective decision making) including seven criteria i.e. costs, delivery time, quality, flexibility, customer proximity, coordination and plant qualification.

Electric mobility is of crucial importance for a sustainable future of individual mobility. Challenges in energy storage with batteries have been identified as a major barrier of a broader electrification of cars. Expensive raw materials, a high scrap rate in production of cells and the lack of a not fully automated process chain lead to high costs of electric cars.
Within this paper a new approach, named Single-Point- Analysis, is presented to setup inline quality assurance in the production of cell foils using optical measurement techniques. The filtering algorithm observes the inter-point distance of each single point in the range of interest. Furthermore a mean distance for each single measurement point is calculated by considering the distances to its direct neighbors. The main focus is the detection of particles and defects like scratches on the cell surface. It is demonstrated that the developed analysis is able to clearly identify these typical failures of cells.

In a world of progressing internationalization of corporate operations, the rise of ever more international valueadded networks can be observed. The configuration and coordination of interdependent production and logistics networks feature enormous potential to optimize the total landed cost of a company's product portfolio. Consequently, the complex structure of a value-added network should not be configured randomly or by comparing only a few alternatives. Optimization in this domain can thus lead to substantial competitive advantages in global markets. Therefore, a consecutive approach is developed that supports the decision-making process to configure a value-added network optimally by especially taking into consideration the specific situation of a multinational corporation. Thereby, the interdependent correlations within the value-added network are modeled and a dynamic mixed-integer linear program for a cost based optimization of the parameters in the network is developed.

To solve the supply chain decision problem of technology selection for electric drive production, the authors chose a game theoretic approach to model and solve the bargaining Situation of manufacturer (OEM) and supplier. The OEM can decide between a same part strategy and a differentiating strategy with increasing sales potential as well as higher complexity and production costs. The supplier has to choose a production technology and can decide between a specialized technology (e.g. punching) and a flexible technology (e.g. laser). Using the specialized Technology the variable costs per piece are lower but every additional variant causes additional tool investments (e.g. punching dies). The interdependence of a supplier’s choice of production technology and ist customer’s decision, regarding the number of different product variants that he wishes to source, is modeled as a non-cooperative game in strategic form. The resulting Nash equilibriums in pure and mixed strategies are determined with respect to the investment costs faced by the supplier, the target market conditions and the cost share passed on to the supplier’s customer.

Many companies no longer act locally within their domestic markets, but have established a global network of worldwide production sites. Due to the long and diversified structures of supply chains and differences in the maturity levels of suppliers, distributed networks develop various fluctuations, in terms of varying product quality and delivery times, which can result in image loss and financial losses to the companies of the network. Moreover, an improperly implemented quality strategy in a network will result in higher costs. The preliminary idea is to make these networks insensitive to such fluctuations by identifying and evaluating suitable quality strategies. Due to the absence of site-specific optimization and the complex structures of networks, it is difficult to find suitable quality strategies for production networks. The complexity in the networks includes unknown defect propagation, limited influence due to decentralized structures and conflicting objectives and unknown inter-relationships amongst the various supply chain members. The research project IQ.net deals with these problems by developing innovative methods, models and practical tools for planning, optimization and control of quality strategies for globally distributed production networks, thus obtaining zero-defect production networks. This chapter aims to discuss various aspects of IQ.net including, the definition of quality in networks, the analysis and evaluation of various systems for managing network-wide quality data considering local versus global data, as well as, three core methods to identify robust quality strategies for specific network configurations.

Today production planning has to deal with highly dynamic markets and increasing uncertainties. Moreover, it has to take into account possibilities of the surrounding production network. By combining a queueing theory model with a stochastic, dynamic optimization approach, a method to support decision making in production planning was developed. Hereby, a Markovian Decision Process is solved to find cost minimal policies as reactions to volatile market demands for minimizing costs due to capacity adaptations, changes in process steps, and locations. The method was applied at two automotive suppliers to finnd suitable system configurations and investment decisions for an uncertain future.

Micro gears are crucial parts of micro transmissions for various applications in industries such as medical, automotive and industrial automation that require highest precision. In order to enhance the lifetime prediction of micro gears, an experimental approach is to be developed at the Karlsruhe Institute of Technology to model the influence of geometric shape deviations and the material structure of micro gears on their lifetime. For this, a highly precise experimental setup is required to conduct abrasive experiments under clearly defined conditions. In this article a suitable experimental rig is presented.

Reconfigurability, flexibility, transformability and agility become key enablers of success. This leads to new business models and the necessity of new concepts for production planning along the whole value chain. Adequate methods have to integrate the possibilities of a migration of the network and the changeability of each single plant. Moreover these approaches should be able to cope with uncertainty and reduce the complexity for the decision-makers to a minimum. Consequently, this paper focuses on two major aspects: ad-hoc rescheduling of reconfigurable plants as well as new innovative business models between equipment or component supplier and OEM. Cyber-physical systems will enable new decentralized and autonomously working production equipment and in doing so, reduce complexity and boost up the speed of possible reactions to market shocks. Component suppliers will enrich their portfolio by new bundling approaches including warranties to their products in terms of risk prevention (e.g. warranties for needed time to react to market changes or bottlenecks).

Increasingly shorter product life cycles at an increasing number of variations call for productive, reliable and quality-oriented production systems and networks which are able to meet the turbulence of global demand especially at an expected higher frequency of economic crises. The following paper presents the development of a theoretical measure for an evaluation that integrates all aspects of a globally distributed production system. The work is based on the latest enhancements of the classic OEE figure of the TPM concept.

The understanding of reliability in production has to be adapted in the context of future production. Herein two levels of reliability have to be addressed. On the level of production systems , reliability considerations are being faced more and more with very flexible, highly connected, and therefore increasingly complex systems. On the machine level however also the reliability of individual machines still has to be analyzed. Therefore the presentation on the one hand examines the impact of future production systems on reliability and which effects may need to be considered in future, e.g. re-scheduling of products in case of a machine breakdown. On the other hand also the reliability of individual machines is regarded and an action is proposed to improve current analyzing by systematically extending the given databases. In this context also the impacts on maintenance strategy planning of machines are considered.

The development and manufacturing of highly precise micro-mechatronic systems, such as MEMS applications, is a challenging task due to the complexity and variety of their manufacturing technologies, as well as their high quality requirements. Within the context of the product engineering process of micro-mechatronic systems, quality inspection by means of production measurement technology is a crucial factor. This paper presents a survey of the challenges regarding quality inspection of micro-mechatronic systems. Furthermore, a Design for Testability approach for these types of products is described and exemplary applications of its implementation are shown.

Life-cycle cost statements become increasingly important for OEMs to stay competitive in today’s global environment. However, OEMs have to create this information from a poor data basis. Generating reliable statistical LCC statements despite the poor data is the methodical challenge. Consequently, it’s crucial to set up an instrument that prepares the data for analysis and simplifies future data collection. Therefore, a database was set up for Licon mt GmbH & Co. KG and the Weibull solution method was adapted by using a weighted pseudo inverse matrix. Both, the database and the adapted method are presented.

Microstructures applied on technical surfaces can lead to a significant improvement of the function of a workpiece. Most of the technical surfaces are preliminary processed, e.g. grinded, before applying the microstructure. Regarding the quality assuran ce, the grinding grooves on the surface can be a barrier when it comes to automatically detect the microstructure and afterwards calculate function oriented quality indicators. Therefore a three-stage noise suppression methodology is presented in this paper using the single point analysis, the Sobel algorithm and the Hough transformation to automatically detect the accurate form of the microstructure in order to enable the subsequent calculation of function orientated quality indicators. These quality indicators can be used to automatically adjust the parameters of the production machine while it is operating.

Advancing globalization leads to growing competition and this in turn results in new requirements in the purchasing process of machines and plants. In order to buy the best production equipment with respect to price and productivity, two crucial criteria are to focus: investment price and quality of the machine. The concept of Life Cycle Costs (LCC) takes into account price and quality of a machine. However, in the machine and plant industry LCC statements are still quite uncertain as the existing database on which they are built is mostly deficient. Based on these data reliability studies on the machine’s lifetime are generated via mathematical methods. A commonly used method is the so called Weibull Analysis. Due to the deficient database this method can be inferior. In order to improve the Weibull method with respect to a deficient database a new mathematical procedure for improved Weibull Analysis is presented.

The economic production of drive components is a major condition for the market success of electric vehicles. To deal with the high number of variants in the automotive industry, market uncertainties and to ensure an economic production, it is necessary to develop flexible production lines which meet the requirements of automotive series production. Based on the development of a production-oriented component design, manufacturing and different measurement methods have to be examined and enabled to readiness. Moreover, simulation-based classification models will be used for the final design of the production lines.

Sustainable individual mobility can only be achieved by reducing CO2 emissions. An option for achieving this objective is to reduce the mass of vehicles, which is forced by the trend towards electric vehicles and by new CO2 regulations. Fiber reinforced plastics are a material group, which is highly suitable for lightweight car design. However, due to the current low automation rate and high production costs the material is not widely used. In particular, the automation of the draping-process - the forming operation of semi-finished textiles - has to be developed. Imperfections, which occur in this process step, can influence the performance of the part in a dramatic way. At the moment, these defects are only detected at the end of the entire production, which leads to high costs. This paper will show how the integration of inline metrology can help to reduce the scrap rate of the parts.

This paper presents an agent-based risk management approach to manage quality risks in global supply networks. The presented methodology blends qualitative and quantitative approaches to the exploration of quality risks in global supply networks by incorporating case study and agent-based modelling methodologies. Manufacturing companies are becoming part of global fragmented supply networks due to the increasing operational specialisation. One threat in these multiple actor networks is the risk that product quality standards are not maintained. The quantification and mitigation of this risk is theoretically and practically challenging due to the special characteristics of supply networks like varied objectives of participating actors or decentralised network governance. A two-step methodology has been developed to identify and evaluate the quality risks and then evaluate the effectiveness of possible mitigation measures. This approach is based on an agent-based simulation model that simulates the impact of quality risks and the acceptance of mitigation measures.

Today there is a strong innovation competition; this is why the number of product models constantly increases and the reduction of product life cycles causes a more frequent occurrence of production ramp-ups. Therefore, it is inevitable that the existing resources, especially human resources should be used efficiently in order to ensure an ideal ramp-up. Hence, the planning of these resources has become an important challenge also in a ramp-up. This paper presents an approach developed at the Institute of Production Science (wbk) of the Karlsruhe Institute of Technology to optimize the forecast of personnel requirements during ramp-up. It describes a method providing support to the calculation of the necessary manpower for every single ramp-up phase in order to realize an economic optimum. Therefore, the paper focuses on the simulation of the ramp-up process within its dynamic planning variables, organizational basic conditions, its verification and results.

Micro gears as parts of micro transmissions are used in manifold industrial applications. The prediction of their lifetime is crucial to ensure their proper operation. For micro gears, geometric shape deviations and material defects have a significant influence on their lifetime. In the presented approach a model for the predition of the lifetime of micro gears is proposed which depends on their geometric shape deviations and material defects. The model is developed based on systematic abrasive experiments, geometric characterization of the micro gears by means of CMM and CT measurements and Weibull analysis.

In the field of cell and battery production today is manufacturing companies are faced with even more intense competitive conditions. Production costs need to be reduced and at the same time the quality of the products have to be improved to succeed in dynamic and global networked markets. Therefore, the reduction of scrap while increasing the level of automation shows great potential. For this purpose it is necessary to assure the quality of products and processes with methods and procedures that can be used in process and in cycle time (the so-called in-process quality assurance). Fulfilling These requirements ensures the high level of automation and the strongly related productivity. The non-conformity rate can be reduced additionally, because changes in product and process characteristics can be identified as early as possible. Consequently, corrective action can be taken before producing deficient products. In order to check as many detailed features as possible, various methods are used in this context to analyze the measurement data. The results strongly depend on the choice of appropriate parameters and thus, strongly depend on the user. The challenge here is the implementation of an automatic measurement data processing, to allow a user-independent, objective and comparable evaluation of measurement data. The main challenge in providing a method for the automatic quality assurance of Li-Ion-Cell surface can be seen in the fact that defects cannot be evaluated by observing the surface with only one optical sensor. With a complete width up to 400-600 mm, the cell foil is marked to be 100.000 times larger than the possible defects like e.g. particles on the surface. This directly shows the need for an adaptable sensor system with the ability to scale up the measurement resolution. Therefore a concept of a multisensory system consisting of a laser triangulation sensor (macro dimensions) in combination with a confocal optical sensor (micro dimensions) is developed at the wbk – Institute of Production Science at KIT. Beside the sensor hardware, the algorithms for evaluating the measurement data need to be in focus as well. Regarding the measurement data evaluation, the automatic detection of points with remarkable deviations in e.g. z-direction can lead to a successful filtering of the Regions of Interest (ROI). This filtering stage for measurement data gained by using a laser triangulation sensor is named the Single Point Analysis and it is necessary to evaluate the smaller application area for the confocal optical sensor. In general, the Single Point Analysis observes the inter-point distance of every point within the measurement range. Therefore a mean distance for each single measurement point is calculated by the consideration of the distances to its direct neighbors. This mean distance of each single point is weighted adjustable according to the mean distance of the whole measurement point cloud. Due to the regular shape of the measurement point cloud by using ptical sensors, all deviations in z-direction of the measurement points can be observed using this algorithm.

Microstructures applied to the surface of a friction bearing are able to improve the behavior of the part. Due to the challenges regarding the production processes of microstructured surfaces an automated and user-independent in-line quality assurance can make a contribution to improve the production processes significantly. Therefore a three stage measurment filter was developed in order to automatically detect microstructures on the surface even under the restriction of a bad signal-noise ratio.

Vorstellung der Empfehlungen und Entwicklungstendenzen in der Produktionstechnik mit Fokus Leichtbau und Elektromobilität beim Workshop eNOVA Strategiekreis Elektromobilität am 26.06.12 in Berlin.

The paper proposed shows a method to optimize spare part provision and maintenance strategies based on the development of appropriate cost-functions and statistical load-dependent failure prognosis.
In order to strengthen their position in the global market, enterprises in mechanical and plant engineering need to differentiate themselves from their competitors. In the machine engineering segment, it is first and foremost the spare part provision and the maintenance that provides machine producers with an interesting opportunity to gain competitive advantage. This paper presents a systematic approach to spare part provision and maintenance delivery at optimal cost which is based on the structural field data of the machines, their operation conditions and their failure data. The starting point is a structured analysis of the machine pool, spare parts and their provision, in order to be able to parameterize their characteristics. A prognosis of the demand of spare parts and maintenance activities can be delivered via a load-dependent reliability analysis. The reliability analysis uses accelerated life testing models.
This work will focus on a methodology which uses an optimization model that assigns an appropriate spare parts provision and maintenance strategy. The goal of the main optimization is to reach the highest possible service level at a given cost and vice versa. On the one hand, minimizing downtimes through elevated spare parts stocks leads to an increase of carrying costs. On the other hand, a decrease of spare parts stocks bears the risk of deficient parts, longer downtimes and thus higher downtime costs. Therefore, the objective is to develop an optimization model, which allows an optimal allocation of spare part provision and maintenance strategies in terms of availability and costs. In order to achieve this objective, first of all a holistic decision model is formulated. So as to finalize the decisions on a well-grounded base, the different strategies are subsequently transformed into monetary criteria. Finally, an integrated optimization model and the formulation of appropriate resolution methods for identification of the optimal allocation for the service strategy are presented.

By focusing on core competencies and the utilization of international location advantages such as access to low-wage labor and local sales markets, global production networks are becoming increasingly complex. The key for control is a changeable production network that can change within preconceived solution spaces for the dynamic challenges. The presented article describes an approach for the strategic planning of global changeable production networks, based on future scenarios and a multi-objective optimization to identify the most favorable network configuration. The final result is a production network, which can be changed into network alternatives to control dynamics and positively utilize globalization.

Manufacturers have pursued green machining strategies, such as process time reduction, to address the demand for environmental impact reduction. These strategies, though, increase the stresses on the manufacturing system, which can affect availability, service life, achieved part quality, and cost. This study presents a total cost analysis of process time reduction for titanium machining to holistically consider the implications of such strategies. While the results suggest it may not be a viable green machining strategy for titanium machining, the feasibility of process time reduction as a greening solution is highly dependent on the functionality of the finished part.

Integral, global sourcing processes covering everything from procurement portfolio analysis to supplier development for qualification as a series supplier provide companies with a solid basis to capitalise on cost-based and competitive advantages. The approach developed at wbk Institute of Production Science is particularly suitable for small and medium-sized enterprises (SMEs). Using the approach, companies will be able to select low-cost country (LCC) procurement objects based on quality criteria and to evaluate LCC supplier development on a dynamical basis. Within the Global Sourcing Process for LCC, the strategic planning process determines the optimal configuration of the three fields of action - procurement object, procurement market and the company’s own abilities. After a procurement object at a particular procurement market is chosen, the dynamic evaluation of the supplier’s qualification determines the monetary advantage of an investment within this supplier cooperation.

Due to the rising technological variety, complexity increases which cannot be met by today’s approaches of flexible and versatile systems. Furthermore, it can be supposed that in the future today’s usual quantities in series production will not be achieved for all kinds of drive trains and that for this reason some powertrain components might be produced below a “critical” quantity. Technological variety and dynamics require flexibility of scales and beyond that high modularity in order to be able to react to modified process steps by means of product- or production-related innovations.

In order to position yourself successfully in the market of machine tools and plants, it is important to gain an advantage over your competition by using novel concepts in the service sector, for example the spare part provision strategies. The proprietary service structure must therefore be assessable. An effective adduction therefore requires a well-grounded planning methodology that facilitates economic progress. This presentation shows a systematic and practical approach to spare part provision at optimal cost, which is based on the structural data of the machines in the field, their operation conditions and their failure data. Through statistical reliability analysis and the integration of load impacts, a more precise prognosis of the spare parts demand can be achieved. The resulting choice of the optimal spare part provision strategy forms the essential part of the presented methodology.

Due to the decreasing in-house production depth and the ongoing trend to internationalization, manufacturing companies are becoming a part of increasingly large supply chains. As a result, the influence of the individual companies on the quality of their products decreases. As quality is one of the key success factors for a manufacturing company,cross-company quality management is becoming more important. To assure quality in the supply chains, an applicable approach depends on several factors like product characteristics, the power of the single actors in the supply chain as well as the supply chain members’ individual target systems. Thus, companies need to identify an individually fitted quality strategy for their supply chain in a systematic way. Therefore, a holistic method has been developed to identify relevant quality parameters for a specific company systematically. The method is based on an agent-based simulation model that simulates the impact of quality problems from tier-n suppliers on a company´s results as well as provides the controllability of suppliers with the help of several quality management measures by consideringtheir individual target systems.

Global business activities of companies grow continuously because cost savings must be achieved and new markets must be tapped into. Today’s companies face the challenge to either satisfy local markets with their existing product portfolio or to develop locally adapted products. These products must not only be adjusted to the individual requirements of the customer but must also realise cost reduction potentials. Such an investment project in the form of product adaptations has to be calculated and evaluated at an early stage. This paper presents an approach to use the real option analysis in order to include uncertainties and flexibility during the development phase. Using this approach industrial companies are capable to identify the cause and effect relationships between product design and production technology adaptations, to calculate the costs of these adaptations and to evaluate the investment project regarding uncertainties and flexibility.

Die Entwicklung, Produktion und Qualitätssicherung urgeformter, mikromechanischer Bauteile und Systeme bewegt sich außerhalb existierender Normen und Richtlinien. Daher ist es wichtig dem Konstrukteur Gestaltungshilfen bereitzustellen, da valide Grundlagen zur Gestaltung dieser Bauteile fehlen. Durch die Fertigungsverfahren weisen die Bauteile, bezogen auf ihre Größe, hohe geometrische Abweichungen auf. Diese stammen u. a. von unterschiedlicher Schrumpfung der Endbauteile durch das Sintern. Im Bereich der Qualitätssicherung können Prüf- und Messverfahren aus dem Makrobereich nicht ohne weiteres für den Mikrobereich herunterskaliert werden. Demzufolge ist es zur Unterstützung des Konstrukteurs wichtig, angepasste bzw. neue Methoden bereit zu stellen, die Aussagen über die Funktionsfähigkeit des zu entwickelnden Systems schon in frühen Phasen der Produktentwicklung erlauben. Diese Probleme können auch mittels Simulation gelöst werden, wenn diese die während des gesamten Entstehungsprozesses entstandenen geometrischen Abweichungen berücksichtigt.

The majority of industrial companies has implemented lean production methods to reduce costs and faulty parts, as well as to meet production deadlines. In order to justify the efforts of such an implementation or the adaptation of production systems in a changing, turbulent business environment, approaches forecasting the success with respect to costs including well-known interdependencies of lean production methods are needed. This paper presents a four-step approach that initially assesses the capability of certain lean production methods, simulates and valuates the effects of such an implementation, and hedges the lean advanced production system against a volatile environment. Using the proposed approach industrial companies are capable of both assessing increased performance with the help of lean production methods monetarily and of identifying thresholds indicating needed adaptation of a production system.

To provide high-class quality technical services to machine and plant clients, machine producers must provide abundant service resources enable adherence to service agreements. Therefore, this paper defines a dynamic characteristic of the serviceability and shows a method how this characteristic can be predicted and optimized through a simulation of the reliability of machine components. In addition, the implementation of a software package is described and a subsequent case study is presented, that employs the methodology and the simulation of the derived serviceability calculation.

Since every company has its own performance targets, the individual interest in achieving high punctuality of delivery dates and in controlling other influencing factors like fulfillment of quality requirements may vary between the supply-chain entities. To maintain high delivery punctuality and eliminate delays due to quality issues, cross-company balancing of target discrepancies and quality management is becoming a key success factor. Given that an applicable approach depends on factors like the power of the single actors in the network, individual target systems, and product characteristics, companies have to find an individually fitted strategy to control their supply-chain. Therefore, an agent-based supply-chain model was implemented to simulate the behavior of supply-chain entities related to their target systems, the influence of quality problems from tiern suppliers on company results and the controllability of suppliers by incentives and quality management measures.

Due to decreasing in-house production depth, industrial companies are becoming part of an increasingly large supply-chain. To maintain product quality and to protect the company against image problems, crosscompany quality management is becoming a key success factor. Since the applicable approach depends on factors like the power of the single actors in the supply-chain, individual target systems, and product characteristics, companies have to find an individually fitted quality strategy for their supply-chain. Therefore, a supply-chain model was implemented that simulates the influence of quality problems from tier-n suppliers on company results and the controllability of suppliers by quality management measures using software agents.

This paper presents an approach which supports decision making in production planning with uncertainties. In current research there is no integrated view of the strategic planning of production networks and the operational planning of processes within a plant. Consequently this approach consists of two steps. First, the manufacturing costs of units in an embedded manufacturing system are analytically calculated based on queueing theory. As a second step, a Markovian Decision Process is solved to find cost minimal reactions to volatile markets for the optimization of the manufacturing system due to capacity adaptations, changes in process steps, and locations.

Fiber-reinforced plastics like sheet molding (SMC) or bulk molding compounds (BMC) offer the ability to reduce the overall weight of products for individual as well as public transportation concepts like motorcars, buses and trains without decreasing passenger safety. A fundamental obstacle on the way to lightweight mobility can be seen in the total production costs of fiber-reinforced plastics. Beside the continued automation of the production processes, advanced quality assurance also offers several chances for contributing to cost reduction efforts. The first approach presented in this paper should focus on the avoidance of producing scrap by providing a systematic method for the quality assessment of produced semi finished SMC/BMC batches. This assessment is processed by the calculation of a quality index and its transformation into the degree of fulfillment. Based on the degree of fulfillment, it can be determined if the produced semi-finished SMC/BMC batch is deliverable to the customer (or to the next process step).

The growing demand to reduce environmental impacts has encouraged manufacturers to pursue various green manufacturing technologies and strategies. These solutions, though, may have a direct impact on several productivity metrics including availability, quality, service life, and cost. This study presents an approach to evaluate the trade-offs between the environmental, performance, and financial impacts of green machining technologies by combining green manufacturing principles into life cycle performance evaluation. The approach is validated by investigating the implications of reducing the processing time by increasing the cutting speed and chip load to green a horizontal milling process.

The estimation of trustable reliability figures for machine tools is a considerable challenge. The main reasons are the sparse availability of relevant components’ lifetime data as well as the load-dependence of reliability. The proposed paper presents a method to estimate increasingly trustable load-dependent reliability figures for machine tools using design information to estimate the reliability if no field data is given, service knowledge of an existing service department which monitors field maintenance of the products and documented field data of spare parts sales, service and maintenance activities.

Zur Steigerung der Effizienz bei der Einführung neuer Produkte sowie zur Beherrschung der entstehenden Produktvielfalt müssen Produktentwicklung und Produktionssystemplanung frühzeitig synchronisiert werden. Dadurch wird versucht, das Spannungsfeld zwischen Qualität, Kosten und Zeit in eine ausgewogene Balance zu bringen. Mit Hilfe der Methode Axiomatic Design wird der Entwicklungsprozess effizient strukturiert. Um unterschiedliche Produktionssystemkonzepte frühzeitig vergleichen und bewerten zu können, ist eine Analyse des Kostenverhaltens im Hinblick auf Schwankungen der prognostizierten Absatzmengen der einzelnen Produkte von hoher Bedeutung. Neben der Entscheidungsunterstützung bei der Produkt- und Produktionssystemplanung dient eine genaue Kenntnis der Herstellkosten zur Absicherung von strategischen Markt- und Preisentscheidungen. Zulieferer müssen darüber hinaus Jahre vor Produktionsbeginn verbindliche Preiszusagen abgeben, so dass eine möglichst genaue Kenntnis der Herstellkosten zum entscheidenden Wettbewerbsvorteil werden kann.

Concerning Industrial Product Service Systems (IPS2) in machine engineering, the challenge for the supplier exists in the determination of the expenses for the provision of the included services over the life cycle of the IPS2 before the start of contract. Thus, in this paper an approach is presented which explains how a supplier of an IPS2, which consists of a machine together with a warranty of availability, can determine his expenses for the warranty. In doing so, the underlying actual operating- and load-dependent failure behavior is taken into account to estimate the supplier´s serviceability to provide the warranty.

Micro-manufacturing processes are often characterized by unknown correlations between process parameters and quality characteristics. Due to the large amount of process data a systematic approach is needed. This paper describes an approach to use data mining methods on production data from micro manufacturing processes. A micro powder injection molding process is used as an example to validate the approach and the results of an initial analysis are presented.

This paper presents a new approach for the Micro Product Engineering Process (µPEP), in which manufacturing data from previously designed and manufactured microsystems is used to aid the tolerancing of new design projects. An existing database of historical production data from the SFB499 was thus adapted to grant tolerance-oriented instead of part-oriented production knowledge access. The new approach was then applied on development of a micro gas turbine.

This paper focuses on the manufacturing of microstructures for the enhancement of friction loaded surfaces of a crankshaft. The studied structures are presented and an approach for the quality assurance of the microstructures is explained. This approach is based on the assessment of the neighbourhood distances between the single measurement points within a measurement point cloud and the application of edge detection to classify the detected form deviations.

Large manufacturing companies demand reliability and availability warranties from their machine tool and plant suppliers. For these suppliers, however, the estimation of these figures is challenging. The challenges include sparse data availability due to short product life-cycles, low production volumes and high variance of different products, as well as the effect of different operating conditions on reliability. This presentation will show a practical methodology with which these companies can estimate increasingly trustworthy reliability figures. Furthermore, it will propose a method for assessing the trustability of the figures.

Decision makers in production planning are challenged by volatile markets and the uncertainties coming along with them. In the presented approach an analytical model of a manufacturing system is defined which takes into account manifold aspects like different routes for each product, stocks, buffers and down-times. Based on this model the manufacturing system is optimized by a Markovian Decision Process. This dynamic, stochastic optimization helps to find cost minimal reactions to uncertain changes in the markets using capacity adaptations, changes in process steps and in locations.

In the last decade, reliability improvement warranties(RIW) became increasingly popular with customers of machine tool manufacturers especially in the automotive industry. These RIWs include long term warranties (for up to 10 years) for reliability figures like the Mean Time Between Failure (MTBF). The long warranty period, the stochastic nature of reliability, unknown operational conditions and uncertainties regarding the reliability parameters of a component bear the risk of cost through high recourses due to low reliability. The paper shows approaches to lower the risks of high recourses in the bidding process and during operation of machine tools. The methods described in the paper are based on statistical failure analysis with the Weibull distribution and Monte Carlo simulation based warranty prognosis. It is shown that with a good knowledge of the infield reliability of their products, machine tool manufacturers have opportunities to not only calculate but also to lower risks of reliability improvement warranties.

Die Automobilindustrie steht vor einem grundlegenden Wandel. Um die weltweite Führungsrolle der deutschen Automobilindustrie zu sichern, muss neben der Entwicklung innovativer Konzepte vor allem die zugehörige Produktionstechnik vorangetrieben werden. Der Vortrag identifiziert wesentliche Herausforderungen und beleuchtet die Aktivitätsfelder Verbrennungsmotor, Elektroantrieb, Speichertechnik und Leichtbau aus produktionstechnischer Sicht. Skalierbarkeit und Flexibilität der Werkzeuge, Anlagen und Fabriken sowie eine neuartige Interdisziplinariat in F&E lassen sich dabei als Schlüsselelemente identifizieren.

The provision of technical services in machine and plant engineering is a profitable field of business for the provider. However, if ambitious availability promises are made, the expenses required in future to deliver the technical service can only be projected with a high level of uncertainty. This paper presents an approach that shows how the serviceability of a service provider for the maintenance of technical components can be evaluated with low levels of uncertainty, and how the resources used to provide the service can be optimized. The result consists in the determination of a serviceability which represents the correlation between the required resources and the number of identical components in the field. It is derived from the times of service provision, which are adapted to the actual operating and load behavior of the components and takes the sustainable planning and optimization of resources for the respective times of service activities into consideration.

The prevailing market and competitive situation requires companies to develop and produce their products fast and cost-effective. To accelerate the development of a new product and its production system a holistic design methodology is developed. Moreover the methodology contains methods which enable decision makers to calculate manufacturing costs per unit and to estimate uncertainties in early planning stages. The developed methods will be implemented in software tools and combined in one common IT infrastructure to guarantee an easy access and a broad acceptance in industrial companies. The methodology and the appendent software tools are developed within the collaborative research project VireS - Virtual synchronization of product development and production system development. First results have been tested at industry partners and are described in this paper.

The increase in the number of product variants is one of the most important challenges of the industry today. It effects almost all departments of a company and is an important cost driver. Therefore, the overall aim of a company is to achieve an optimal degree of flexibility over the whole life cycle of a production system. In early planning stages however the quality and quantity of data is very poor and uncertainties about quantities and variants are challenging. So far appropriate analyses of costs per parts and as a consequence a monetary based decision between possible production system designs cannot be done. Within the framework of the collaborative research project VireS a scientific approach to evaluate different production scenarios in early planning stages was developed and implemented by the Institute of Production Science (wbk) of the Karlsruhe Institute of Technology (KIT). Using a simulation tool called F-One costs can be calculated depending on ranges of quantities and variants taking different kinds of uncertainties into account.

Production in international value-added networks is becoming increasingly important. Companies have to handle and control numerous production sites and suppliers of different regional and cultural background to maintain key success factors as for instance cost and quality. To support companies in planning and controlling their value-added networks an approach for the simulation of production networks under consideration of different target systems for each unit in the network, like production plants, suppliers and also relevant decision makers, was developed at the wbk Institute for Production Science. The unconsidered influences during the implementation phase of network configurations developed with existing simulation and optimization tools are in focus of the approach. Therefore, the simulation model integrates realistic hierarchies, organizational borders and individual target systems.

Today, etended warranties are increasingly popular in the machine tools industry. But weak failure data and time varying loads make it difficult for machine tool manufacturers to estimate the costs and the risks of such warranties. This paper presents a methodology to determine the Value at Risk of warranties for machine tools considering weak data sets and unknown load profiles. The methodology uses random parameters obtained by different sampling methods to simulate the warranty costs using Monte Carlo simulation. As result, the Value at Risk of the warranty for a certain probability is determined.

The demand to simultaneously increase the functionality of devices while decreasing their size and weight continuously offers new fields of application for devices like micro gear drives. To fulfill this demand micro gear drives must continue to become smaller and more accurate. This requires, in addition to stable micro manufacturing processes, a quality assurance of the parts of micro gear drives. A main challenge within the use of micro metrology is the estimation of the uncertainty of measurement of the measurement task to be fulfilled. This article describes an approach for a workpiece resembling standard for experimentally estimating the uncertainty of measurement for micro gears. It shows why such a micro gear standard is required. Additionally, the article identifies demands on such a standard. Also, a proposal for the structure and the shape of the standard is presented. This includes fabrication possibilities and the choice of appropriate material. Essential components of the standard are cylindrical geometries to determine the uncertainty of measurement of the characterization of the profile deviation, helix deviation, and pitch deviation. Also, the increasingly recognized importance of entire tooth flanks for the function of the gear is considered for the proposed standard. Therefore, the standard embodies the surface of an involute tooth flank with the help of the cylindrical geometries to enable the characterization of the entire tooth flank surface. Furthermore, probing strategies for actual measurements with the standard are discussed. The article concludes with a presentation of future work on the micro gear standard.

This paper presents two processes for the reconfiguration of global manufacturing networks - one has been developed in Cambridge and one in Karlsruhe. The processes are based on different research contributions and have been tested and refined in industrial companies. In this paper similarities and differences of the two approaches are identified. Cambridge’s process tends to take a strategic view and covers a wider range of considerations. It focuses more on the design of network options than on the assessment of these alternatives. Karlsruhe’s process addresses a smaller range of considerations, but takes a more detailed point of view. The assessment and test of robustness is focused and carried out with ophisticated mathematical tools. A toolbox of concepts is developed and it is highlighted that company’s characteristics must be integrated to find a fitting process. Possibilities how both processes might support each other and opportunities for further research are discussed.

This paper discusses the effects of measurement uncertainty on part inspection and process evaluation, which is especially important for quality assurance in micro-manufacturing. In order to incorporate the effects of measurement uncertainty on process evaluation, the wbk Institute of Production Science has developed two new process capability indices, cpu and cpku, which are adapted from the cp and cpk indices by adjusting the tolerance range according to the expanded uncertainty of measurement. By doing so, the cpu and cpku indices provide a holistic approach to micro-manufacturing capability in which both the production process and the measurement process are considered as essential elements contributing to the final quality of the product.

This paper outlines a threefold methodological approach integrating dimensional measurement, virtual tests of measured real gears and physical tests of real gears. As a demonstrator for the presented methodology high-loadable microgears made of zirconium oxide are used.

Recently, an increasing number of customers of the machine tool industry have applied life cycle costing (LCC) to compare the cost-effectiveness of different investment options. These concepts have mainly been used to address maintenance costs since these have proven to be one of the most important cost drivers. The approach of life cycle performance (LCP) broadens LCC by considering the relationship between the costs and benefits of a machine over its entire life cycle. With the increasing importance of environmental consciousness, it has become crucial to incorporate environmental impact when evaluating machines. A framework is presented that enables the integration of green manufacturing principles into LCP-evaluation. The role of interoperability within this framework is also discussed.

The development of a new supplier relationship in a low-cost country carries investment risks and can be considered a multi-stage investment project with uncertainties. In turn, the buying company can make use of its flexibility within the project, e.g. exit the supplier development at certain stages to save further investments. This paper presents a real options model developed at the wbk Institute of Production Science to valuate a supplier development under risks and flexibility. Due to a continuous valuation in the presented methodology the forecast uncertainty is decreased significantly. Finally, the methodology is validated by a case study which illustrates a supplier development in South Korea by a global OEM.

The selection of a suitable measurement strategy for micro-dimensional quality features is a task which requires considerable expertise and experience. To aid technicians with the appropriate selection of a sensor and its parameter settings for a given measurement task, this article presents an experience-based user support system. The structure of the system’s backbone, a relational database, as well as the interaction of the technician with the system is described. The support system can lead to improved measurement results while also decreasing the necessary time and effort for the inspection planning process.

Micro gears are characterized by shape deviations caused by micro manufacturing processes, which operate close to physical limits. This paper presents an approach to match micro gears which are afflicted with shape deviations. The approach consists of a geometrical part that couples the dimensional characterization of the tooth flank of a micro gear with a matching simulation and a functional part in which functionally relevant characteristics are derived from functional testing.

A global set-up of production sites and suppliers in an increasingly globalised world provides huge opportunities for companies, such as the development of new markets or the reduction of production costs. In spite of these advantages and the desire of companies to make full use of them, global production has not been mastered so far and its potential has not yet been fully tapped. Global production often results in quality issues or unexpectedly high costs. The technical features of the product to be manufactured have a major impact on whether global production will be successful or not. This article aims at presenting an approach to tapping the potential of low-cost countries by tailoring product design to local needs and, at the same time, to reducing entrepreneurial risks.

Due to the increasing demand for extended warranties and the increasing popularity of preventive maintenance for investment goods, the importance of dependable reliability figures has increased. Reliability figures tend to be more dependable when more failure data are used to obtain them. The low availability of data, however, is a key problem in reliability analysis in the investment goods industry. Reliability figures obtained from only a small amount of failure data can be given only with uncertainty. This uncertainty needs to be assessed. In this presentation a method will be shown that uses the parameter confidence and a Monte Carlo simulation to quantify the risks that arise from this uncertainty. Furthermore, it is shown how this method can be integrated in warranty prognosis and the optimization of preventive maintenance for investment goods.

A global set-up of production sites and suppliers in an increasingly globalised world provides huge opportunities for companies, such as the development of new markets or the reduction of production costs. In spite of these advantages and the desire of companies to make full use of them, global production has not been mastered so far and its potential has not yet been fully tapped. Global production often results in quality issues or unexpectedly high costs. The technical features of the product to be manufactured have a major impact on whether global production will be successful or not. This article aims at presenting an approach to tapping the potential of low-cost countries by tailoring product design to local needs and, at the same time, to reducing entrepreneurial risks.

Low-cost country sourcing (LCCS) offers the opportunity to considerably save costs and enter new attractive markets. In order to tap the potential of low-cost country sourcing successfully, the barriers and challenges coming with it need to be systematically specified and the procurement structures must be oriented towards LCCS. This paper will analyze and categorize the barriers and challenges which are given in literature. Based on this literary analysis, this paper will give recommendations on how to implement different aspects of low-cost country sourcing. The results of a practical example from industry will finally be presented. As part of this, a company’s strengths and weaknesses with regards to LCCS were analyzed by using a checklist which was developed based on these recommendations.

The requests for production systems are changing constantly as a consequence of increasing competitive pressure. Hence, evaluation methods are becoming more and more important. In addition, the effect of influencing factors subject to indeterminate variations needs to be included in the evaluation, and their impact on production costs is to be made transparent. The flexibility and, therefore, the robustness of a production system to market and product specific changes are essential for the economic success of a company. Especially in the early stage of the product development the knowledge about the required flexibility of a production system is of utmost importance. Within this approach an evaluation method is illustrated which allows a quantitative assessment of the flexibility in the early planning stages.

How and where in micromanufacturing process chains the functionally relevant dimensional features of micromechanical components are measured and with which measuring devices is a problem with which manufacturers currently have little experience solving. The goal of this paper is to present a method for determining the optimal quality control plan to assure the quality of dimensional features of micromechanical components with respect to the scrap rate of the production process, the type I and type II errors of the inspection process and the necessary time and cost of inspections. The aforementioned criteria on which the selection of the optimal quality control plan is based are detailed and an object-oriented model of the manufacturing process chain is presented in this paper. Due to the combinatorial nature of this problem and the desire to consider the multiple objectives independently, a population-based metaheuristic approach is proposed to search for the set of Pareto optimal quality control plans with respect to the defined objectives.

Geprägt durch den zunehmenden Wettbewerb fordern die Kunden des Maschinen- und Anlagenbaus verstärkt die Garantie ausgewählter Produktleistungsparameter (wie z.B. Zuverlässigkeit und Verfügbarkeit) sowie bestimmter Lebenszykluskostenelemente als wesentliche Qualitätsmerkmale von Investitionsgütern. Dies bietet den Maschinenherstellern die Chance, den höheren Preis der eigenen Produkte im Vergleich zu den Konkurrenzprodukten aus low-cost Ländern durch die Objektivierung der Produktleistung zu rechtfertigen. Aufgrund des hochkomplexen Ausfallverhaltens produktionstechnischer Maschinen und Anlagen birgt die Garantie derartiger Qualitäts- und Leistungsparameter allerdings große Risiken für die zumeist kleinen und mittelständischen Unternehmen (KMU) der Branche. Ziel des Projektes myLCP (Skalierbare Life Cycle Performance-Prognoseverfahren für den Maschinen- und Anlagenbau) ist es daher, für die Hersteller von Maschinen und Anlagen wissenschaftliche und anwendbare Methoden für die Analyse, Prognose sowie Steuerung der Leistung und der Kosten produktionstechnischer Anlagen (der sogen. Life Cycle Performance) zu entwickeln. Herausforderungen bestehen vor allem hinsichtlich der stochastischen Natur der Zuverlässigkeit technischer Systeme, der Modellierung der Maschinenbelastung sowie der mathematischen Bestimmung des Abschätzungsfehlers von Zuverlässigkeitsprognosen. Diesen Herausforderungen stellt sich ein Forschungskonsortium, bestehend aus vier kleinen und mittelständischen Unternehmen des Maschinen- und Anlagenbaus, dem Institut für Produktionstechnik (wbk) und der Forschungsgemeinschaft Qualität e.V. (FQS).

Die Qualitätssicherung mikromechanischer Bauteile sieht sich drei zentralen Herausforderungen gegenüber: eine hohe Prozessvariabilität, die Überlagerung von Fertigungs- und Messprozessstreuung und die Unkenntnis der optimalen Prüfstrategie entlang der Produktionsprozesskette. Zur Bewältigung dieser Herausforderungen werden drei Methoden vorgestellt. Die hohe Prozessvariabilität eines einzelnen Fertigungsprozesses wird durch einen modellbasierten prädiktiven Regler reduziert. Die Trennung von Fertigungs- und Messstreuung für eine statistische Prozesskontrolle wird durch ein neues multivariates Qualitätsregelkartendesign ermöglicht. Darüberhinaus werden Richtlinien zur Erstellung einer mikroprozesskettenoptimalen Prüfstrategie durch Axiomatic Design entwickelt. Um diese Richtlinien zu verifizieren und um neue Erkenntnisse zu gewinnen, werden die Ergebnisse mit denen einer multikriteriellen Optimierung der Prüfstrategie verglichen.

The collaborative research centre SFB/TR10 is developing and setting up a prototypical process chain for the flexible production and machining of three dimensionally curved extrusion profiles. This paper presents the the process chain and the ongoing research activities aiming to increase the accuracy of the contour of the manufactured profiles.

Due to increasing globalization, customer demands and resource constraints companies are facing growing time, cost and flexibility pressures. This forces them to enter into new forms of organization and cooperation: Value Added Networks consisting of different locations of one company but also including external partners and suppliers are emerging. The challenge is to configure these production networks, to run them economically and to identify and realize potentials for optimization. This article describes an integrated concept for the evaluation of these Value Added Network alternatives to find the best, robust solution for the network configuration concerning the implied dynamics and uncertainties. Therefore a target system consisting of relevant objectives like cost, time, quality or flexibility has to be identified. This target system has to conform to the strategy of the configured Value Added Network (e.g. quality, cost or time leadership). As these targets can be contradictory, methods for multi-criteria optimization have to be applied. To reach a high robustness of the network the approach combines a Monte-Carlo simulation and sensitivity analyses to assess and quantify the possible influences.

This research introduces a method to identify shape deviations of the workpiece and errors in the probing process in coordinate metrology by analyzing the observed measurement points. The approach is based on the statistical analysis of distances between points in the point cloud. Furthermore, the influence of single measurement points is taken into account by quantifying their effect on the result. In the article, the method is explained thoroughly and its application with actual measurement data from a micro-structured workpiece is presented.

Realizing cost saving potentials represents one of the main motives of low-cost country sourcing. The development and qualification of suitable suppliers in these countries though is an expensive and long-term process. Furthermore, low-cost country sourcing incurs higher risks than procuring in the home country as exchange rates, wages and transport costs as well as material costs are subject to changes. The development of a supplier relationship in a low-cost country therefore carries investment risks and can be considered a multi-stage investment project with uncertainties. This article is aimed at the representation of a model developed at the wbk Institute of Production Science, Universität Karlsruhe (TH), for the investment-oriented valuation of supplier development expenditure in low-cost countries on the basis of the real option theory.

In this paper results concerning the quality of micro gears made via dimensional metrology and functional testing are discussed and compared. Thus, possible effects of geometrical deviations on the function can be identified and possible interrelations between standard characteristics like profile deviations and the tangential composite deviation can be indicated and analyzed.

Mere cost appraisals and flexibility assessments will no longer suffice to design and plan production systems over their life cycle. In addition, the effect of influencing factors subject to indeterminate variations needs to be included the evaluation, and their impact on production costs is to be made transparent. To achieve a better planning basis in the future, the influence of uncertainties must be reduced and at the same time the prognosis exactness of the calculated costs must be improved. For a superior illustration of the influence of uncertainties, a purely deterministic approach is no longer effectual. Hence, the flexibility and, therefore, the resistance of a production system to market and product specific changes are determined stochastically within this article.

More and more companies are using lean production methods in order to improve their processes and stay competitive. Due to the fact that lean methods have different impacts on production systems depending on existing characteristics and conditions, they have to be successfully adapted to the specific requirements. This paper shows a transparent structure of interdependencies between lean methods and relevant production figures developed at the Institute of Production Science (wbk), Universität Karlsruhe (TH), Germany. Besides, it discusses a methodology for the simulation-based analysis and optimization of production systems by lean methods serving as forecasting tool for an efficient planning process.

Many companies decide to opt for procurement markets of low-cost countries hoping to benefit from considerable regional differences in factor costs and from lower wages in particular. But not every procurement object can be successfully purchased from low-cost countries. In many cases, the procuring companies are faced with quality issues or costs way beyond the estimate. The outcome mostly depends on the technical characteristics of the respective product. This is a main challenge of low-cost country sourcing resulting from a poor selection of procurement objects. The basic novel approach developed at the Institute of Production Science (wbk) of the Universität Karlsruhe (TH) consists in the identification of factors affecting the selection of procurement objects. These factors are then used as a basis for the development of principles for the selection of procurement objects offering the best potential in terms of quality and project outcome when sourced from low-cost countries.

Aufgrund steigender Kundenanforderungen und kürzer werdender Produktinnovationszyklen wachsen die Teilevielfalt und damit die Komplexität der Ersatzteilversorgung im Maschinen- und Anlagenbau zunehmend an. Häufige Folgen dieser Entwicklung sind Überbestände, hohe Kapitalbindungskosten und teure Verschrottungsaktionen, um hohe Fehlmengenkosten und Konventionalstrafen bei Produktionsausfällen zu vermeiden. Vor diesem Hintergrund ist es notwendig, die Lebensdauer hochwertiger Komponente in Abhängigkeit ihrer betriebsbedingten Belastungen zu ermitteln, um rechtzeitig das geeignete Ersatzteil bei einem Ausfall bereitstellen zu können. Im Rahmen eines umfassenden Ersatzteilmanagements ermöglicht die ausfallgerechte Bereitstellung von bestimmten Ersatzteilen eine hohe Ersatzteildisponibilität bei gleichzeitiger Realisierung von Einsparpotentialen.

Not every product can be successfully sourced in low-cost countries. Disadvantageous cost structures or extremely complex workpiece designs are the most frequent reasons for failures. A design that has been tailored to low-cost country sourcing offers the possibility of increasing potentials while reducing risks and costs at the same time. The wbk Institute of Production Science at the Universität Karlsruhe (TH) developed a new approach which ensures that the product design meets the requirements of the supplier. This paper identifies the factors influencing the design, deduces basic principles and illustrates guidelines for an adapted product design.

In coordinate metrology results are based on a set of probed points from the workpiece surface, which are evaluated with the use of ideal substitute geometries. Shape deviations of the workpiece lead to non-uniform influence of single points on the result. In the article, a method to analyze the influence of single measurement points on the result and to compute the uncertainty of the evaluation is proposed. The statistical resampling technique -The Jackknife- is adapted for use with CMM point clouds. This technique allows the bias and standard error of the measurand to be estimated. The outcome is analyzed with computer simulations, whose results are presented in this article.

According to recent investigations the sale of spare parts is a considerable key business in the after-sales market. In the machine building industry the profit margins of the service and spare parts business exceed the classical product business by a factor of ten. To reduce the probability of cost-intensive breakdowns a constant availability of spare parts is necessary. The earning potentials in the after-sales market can only be exploited if customers are supplied with specific spare parts within stipulated reaction times. However especially in the machine building industry, the factors that influence the demand forecast of spare parts are diverse. The high number of models and variants of the machines and the simultaneously small number of sold units complicate an accurate prediction. Furthermore, the service life of single components is influenced to a great extend by different and variable loads depending on the production processes. Hence, most companies have to maintain high and expensive spare parts inventories to assure a certain availability. The presented approach aims at analyzing and predicting the service life of components depending on the load that is applied. This information is combined with logistic aspects such as delivery times or stock strategies. By using the approach, it is possible to predict the demand of spare parts more accurately. Cost optimal strategies for the provision of spare parts can be developed and evaluated. This helps companies to reduce their expensive inventories of spare parts.

Manufacturers increasingly integrate the suppliers of their production equipment into their maintenance activities in order to improve the reliability and availability of their machinery. This forces suppliers to increase their knowledge of the failure behavior of their products. However, the failure data delivered to them by their customers often lacks information about the operational conditions of the machine tools. Since these operational conditions are highly variable and have a large impact on the reliability of the machines, it is important to gain knowledge of them. The approach being presented uses the Mixed Weibull and the Cumulative Damage models to estimate the different operational conditions from mixed failure data and uses field data collected from a machine tool component.

A challenging task for a systematic quality assurance is the characterization of micro gears via metrology. Additional factors in micrometer dimensions such as significant shape deviations of the produced micro gears increase the complexity. This paper describes an approach for a three-dimensional surface characterization of the tooth flanks of micro gears. A three-dimensional point of view defines the functionally relevant tooth flanks as a surface in contrast to the common definition via two-dimensional characteristics. Additionally, this paper describes how these flank characterizations will then be used for matching micro gears afflicted with shape deviations for functioning gearings.

This paper presents an approach to the dynamic optimization of the preventive maintenance schedule for machine tool components during operation based on the actual operating life and the respective load profile. Therefore, a stochastic model based on the Weibull Cumulative Damage Generalized Log-Linear Model and the Monte Carlo Simulation is used. Furthermore, the effect of the dynamic optimization on component selection for different maintenance strategies is taken into consideration. The ideal strategy can be selected from corrective, preventive and condition-based maintenance for every component of acomplex system.

A high and constant machine reliability in combinationwith low life cycle cost is the key challenge for today’sproduction. Equipping highly integrated production facilitieswith robust components and monitoring functions combinedwith the applicable technical services contributes significantlyto guaranteeing machine reliability. In this context, bindingreliability predictions are demanded within the scope ofreliability-based warranty contracts, life cycle cost-driven bidsor service contracts. This article presents an approach whichaims at analyzing and predicting the reliability of machinesand their components depending on load that is applied. Thisresearch focuses on fatigue failures, caused in componentsunder the influence of fluctuating loads. However, the mainmethodology can be applied with some modifications to otherfailure modes as well. By integrating suitable methods andinformation from different sources, this approach helps toachieve a more accurate reliability analysis and predictionwhen very little field data is available. This reduces themanufacturer’s risks arising from the aforementionedcontracts. Additionally, the operators of production facilitiesgain a greater level of certainty in production planning, in thescheduling of preventive maintenance activities and inplanning the provision and storage of necessary spare parts.

In order to stay competitive in the globalizing markets with fast changing conditions and requirements, small and medium sized enterprises aim to implement methods and tools of the lean production philosophy, which already lead to enormous efficiency improvements in large companies. But these lean methods cannot easily be transferred as they have a different impact on the production system depending on the existing circumstances. The analysis and quantification of these interdependencies is subject of the current research work at the Institute of Production Science (wbk) in Karlsruhe. Using material flow simulation and parametric optimization, efficient combinations of lean methods for small batch productions can be determined under consideration of different target systems. This approach of the simulation-based optimization of small batch productions applying lean methods is explained in the following article.

This paper describes a methodology for comprehensive procurement market selection for sourcing from low-cost countries. The basic novelty of this approach consists in allocating potential procurement markets for specific procurement objects matching the capabilities and requirements of the buying company in question. The methodology includes four major steps: First, profiles of the potential procurement markets, the objects to be purchased and the buying company are generated. Then, the interdependencies and cause-effect relationships of the criteria of these three profiles are analysed. Afterwards, the allocation is completed by two comparisons based on the delta values of each criterion of procurement market and object and procurement market and company, respectively. This serves to verify the congruence between market and company and between market and procurement object. Finally, the countries are ranked by procurement object suitability and company suitability.

For the measurement of micro mechanical workpieces multi-sensor coordinate measurement machines are widely used due to their flexibility. Because of this flexibility many decisions regarding the measurement strategy have to be made. The planning process demands a lot of knowledge and experience from the user. This is especially true for the measurement of micro structures, since many effects need to be considered. In this talk challenges in micro coordinate metrology and solutions to support the user during the planning process are presented.

The paper shows the application of the statistical resampling technique called "TheJackknife" to compute uncertainties of measurement results in coordinate metrology,introduced by the reduction of a point cloud to an ideal substitute geometry. Inaddition, a method is proposed which uses the computed Jackknife data to analyze theinfluence of single touch points on the measurement result. Exemplary, the procedureis applied to a point cloud of a 2-dimensional circle.

Small and medium-sized companies encounter enormous difficulties when trying to implement so-called lean methods according to the role model of the Toyota Production System. This is caused by the varying effects of lean methods on production figures depending on the production conditions concerning product variety and volumes, variation of process and set-up times etc. Thus, there are no general guidelines for the â??best possibleâ?? implementation of these methods in a small series production. This article shows an approach to analyze and evaluate the influence of lean methods in small series productions based on quantified interdependencies with the relevant production figures.

Due to the higher number of significant influencing factors (microstructure, temperature etc.), micro manufacturing processes are subject to higher variability than processes in the macro range. With regard to micro cutting, the roundness of the cutting edge and microstructure properties of the machined material have a great impact on the achievable surface quality. In case of sequential removal the cutting process affects surface layers that, other than the base material, are already hardened from a former removal process. Only traditional control charts will detect process shifts (e.g. caused by material inhomogeneities) but cannot take care of continuous process improvement. Therefore, a control loop that adaptively adjusts the process parameters to the changed surrounding conditions for each cycle is required. By using an extended Victor-Kienzle model, the improvement in surface quality through control of the cutting force, cutting edge radius and cutting speed is shown empirically.

Globally operating companies face the challenge of an optimal and efficient configuration of their value added network. The participating sites, partners and suppliers have to be selected according to their specific capabilities. Thereby the configuration has to respect not only the actual status but also the different dynamic influences of the nodes of the network themselves but also of the connections between them. This article presents an approach for the configuration of global value added networks using Business Capabilities with special consideration of the ramp-up behaviour of the single elements.

This article describes a concept for the configuration of global Value Added Networks based on Business Capabilities. Business Capabilities are used to describe the planned added value and the abilities of the existing nodes (own sites or partners) within the network, without having to define used technologies and resources. A matching of Business Capabilities needed for the planned added value and of Business Capabilities provided by potential nodes, allows an assignment of added value content to these nodes. On node level and thereby decentralized the Business Capabilities can be combined with suitable technologies and resources. This combination is defined as Value Added Module. By composing needed Business Capabilities or Value Added Modules, different network alternatives can be configured and compared. These alternatives of the Value Added Network can be evaluated based upon a predefined target system. The article presents the concept of Business Capabilities and an outlook to a supporting IT-solution.

Decreasing product life-cycles and resulting market pressure to launch newproducts in continuously decreasing time intervals are describing todayâ??sautomotive industry [1]. Therefore production ramp-ups are gaining more andmore importance. Production ramp-ups are characterized by new products, newproduction technology and instable business processes. One main problem toachieve planned output and efficiency targets is the availability of human andtechnical resources during production ramp-up. In this paper, a new simulationbased resource planning method for production ramp-ups is introduced. Themethod supports resource planning during production ramp-up based on businessprocesses,quality of production processes and operational availability ofmachinery. Next to theory a prototypical implementation and simulation results arepresented. This research project is sponsored by the German Research Foundation(DFG).

The core challenge of an industrially applicable and economic production of wear resistant micro components and systems is the establishment of both robust and flexible manufacturing process chains. In order to guarantee those stable process chains, manufacturing processes have to be controlled and continuously improved by an effective and fast interfering operational quality assurance that is adapted to the micro-specific framework. Since tolerances of micro-structured parts are in the micro- and sub-micrometer range, geometric measurement results have to meet high requirements in terms of precision and reliability. Therefore, in order to control manufacturing processes in micro production based on measurement data the increased importance of measurement uncertainty and measurement variation has to be considered. Measurement data show an interference of measurement and manufacturing distribution and can lead to wrong decisions when deciding whether the micro manufacturing process is in or out of control. Thus, the focus of the paper lies on continuously monitoring, controlling and separating measurement and manufacturing variation in a flexible, simple and reliable manner. Therefore, a new type of a multivariate µ-EWMA control chart developed at wbk is discussed and benchmarked with traditional control charts. The paper concludes with first results of the application of the multivariate µ-EWMA chart in micro production environment.

Die wesentliche Herausforderung für eine industriell umsetzbare Mikroproduktion ist die Entwicklung robuster und flexibler Fertigungsprozesse. Um Robustheit und Flexibilität auch in Mikrodimensionen zu realisieren, müssen die Fertigungsprozesse durch eine schnelle, fertigungsnahe und den mikrospezifischen Besonderheiten entsprechende Qualitätssicherung kontinuierlich geregelt und verbessert werden. Bisher sind Mikrofertigungsprozesse durch eine hohe Variabilität aufgrund der höheren Anzahl signifikanter Einflussfaktoren bestimmt. Darüber hinaus liegen die Toleranzanforderungen mikrostrukturierter Bauteile im Mikro- und Submikrometerbereich, was höchste Genauigkeitsanforderungen an die Messverfahren stellt. Um Mikrofertigungsprozesse basierend auf Messdaten zu regeln, muss der erhöhten Bedeutung der Messunsicherheit und der Messstreuung im Vergleich zu den geforderten Toleranzen Rechnung getragen werden. Messdaten zeigen dabei immer eine Überlagerung von Fertigungs- und Messstreuung, die im Falle höchster Toleranzanforderungen zu falschen Entscheidungen bezüglich der Annahme oder Ablehnung von Bauteilen führen kann. Daher liegt der Fokus der vorliegenden Forschungsarbeit im Rahmen des SFB 499 auf der kontinuierlichen Überwachung, Regelung und Trennung von Fertigungs- und Messstreuung mit Hilfe statistischer Werkzeuge. Es wird sowohl ein neuartiges Qualitätsregelkarten-Design als auch ein Regelkreis zur Kombination von Statistischer Prozessregelung und Statistischer Modellierung, welche im Rahmen des SFB 499 entwickelt wurde, vorgestellt und diskutiert. Der vorliegende Artikel schließt mit ersten Ergebnissen über den Einsatz der statistischen Werkzeuge im mikroproduktionstechnischen Umfeld.

High precision engineering has a great technological potential regarding the manufacturing of micro technical products. In this field micro cutting is due to its flexibility and the possibility to produce complex three dimensional geometries in a broad variety of different materials of special importance. However, milling and turning in micro dimensions follow special rules caused by size-effects. Successful micro cutting depends on reliable processes and therefore on the knowledge about parameter adjustments and process characterization. By means of micro cutting test series and statistical analyses effects and interactions of process parameter variations for work piece material, cutting edge radii, cutting speed, and depth of cut were identified and mathematical quantified. The results show a significant influence of the mentioned factors on the response variables. Therefore, a linear model for specific cutting force and surface roughness is proposed. Furthermore, the findings are compared to the empirical cutting model of Victor-Kienzle in macro dimensions.

The ubiquitous globalization, which opens up new markets with their specific local conditions and labor costs, as well as the increasing pressure regarding time, costs and flexibility lead to the decentralization of the value added. The resulting global value added networks, consisting of company-owned and external sites as well as logistic partners, have to be configured, operated and optimized. An important criterion for these networks is their ability to a fast and efficient ramp-up. This article presents a concept to assess and select potential value added network’s nodes (sites or external partners) according to their ramp-up performance to achieve an optimal configuration of the network.

Due to dramatically reduced development times and product-life-cycles the control of production ramp-up isan important criterion for the companies' success. The aim of the shown research project sponsored by theGerman Research Foundation (DFG) is the optimization of ramp-up, by developing a solution method whichallows a quality-simulation of the instable production processes during ramp-up. To achieve this, the expecteddevelopment of the quality-capability of the instable production-processes will be anticipated by the exampleof metal cutting manufacturing. Based on standardized elementary processes, the developed simulation forecaststhe capability of the production-system and the variable needs of resources during ramp-up.

The core challenge of an industrially applicable and economic production of wear resistant micro components and systems is the establishment of both robust and flexible manufacturing process chains. In order to guarantee those stable micro chains manufacturing processes have to be controlled and continuously improved by an effective and fast interfering operational quality assurance. The key instrument of an operational quality assurance consists in controlling the manufacturing processes via control charts. Due to the stochastic performance of micro process chains new types of quality control charts adapted to micro production constraints such as measurement uncertainty have to be developed and are discussed in the following.

Production ramp-up has become one of the most decisive factor influencing profit and market share of a new product. The big challenge in production ramp-up is to reach the planned output by reducing time and costs. Over the last years product range is increasing and life cycle of the products is decreasing. This circumstance makes a controlled production ramp-up more difficult and therefore more and more ramp-ups are running out of their financial budgets and their time schedules. One of the most important influences on time and money is the quality development during production rampups. The ability to control the quality while increasing the output is the key success factor for an effective ramp-up [1]. In this paper a method is introduced which allows a quality prognosis during production ramp-ups by using simulation methods. This simulation model is based on business-processes and supports the ramp-up manager to forecast qualityrates and machine availability during the production ramp-up. Thus this tool can support the ramp-up team to stay within their financial budgets and time schedules.

Ramp-up of a new production system has become a decisive factor influencing protit. The reason is an incessanlly growing product range with conslantly decreasing life cycles therefore ramp-ups have to become more efticient and faster. Characteristic for nunp-up processes are instable business pwcesses, leading to a !arge number of quality problems. The approach of Overall Equipment Effectiveness (OEE) simulation presented in this paper allows simulating the inslabte state of a procluction system during ramp-up. Thus, tbe production planncr is supported cluring ramp-up planning and the actual ramp-up period. Using OEE Simulation the planner can identify deviations from the target ramp-up cprve at an early stage.

‘Multi Enterprise Scheduling’ considers the temporal allocation of activities to resources. As soon as the specific targets and additional conditions have been achieved, the most suitable enterprise to execute the activity must be chosen. In the following article, the activity model presents the connections and logical sequence of the activities within the company overlapping business processes. The Organization units are identified in an Organizational and Resource Model. In the concept they are represented through Multi Agents, namely the Activity Agent and the Resource Agent. To meet the requirements of communication and cooperation across companies, it is attempted to implement this agent technology with web parts.

Die wbk-Herbsttagung hat sich als wichtigste jährliche Veranstaltung am wbk etabliert. Dieses Jahr fand sie am 27. Oktober 2011 zum Thema ?Produktions-technische Herausforderungen der Elektromobilität? statt. Hintergrund für die Themenwahl ist der Wandel in der Mobilität von rein auf Verbrennung basierten Antriebskonzepten hin zu voll-elektrischen Fahrzeugen und den damit verbundenen Speichertechnologien.

Sowohl in der Automobilindustrie, im Gesundheitswesen als auch im Bereich der Unterhaltungselektronik wird ein steigender Bedarf für Mikrozahnräder beobachtet [1, 2, 3]. Sie werden vorwiegend in Mikrogetrieben eingesetzt, um mechanische Leistung zu wandeln. Die Entwicklung und Produktion mikromechanischer Bauteile ist jedoch mit vielfältigen komplexen Anforderungen verknüpft. Die mit derzeitigen Mikro-Fertigungstechnologien erreichbaren Toleranzen setzen einer präzisen Funktionserfüllung beliebig gepaarter Mikrozahnräder klare Grenzen. Die tatsächlich gefertigten geometrischen Abmessungen mikromechanischer Bauteile liegen in derselben Größenordnung wie derzeit erreichbare Fertigungstoleranzen, sodass starke Schwankungen bezüglich der Abmessungen und entsprechende Gestaltabweichungen beobachtet werden [4]. Eine Funktionserfüllung in der vorgesehenen Qualität kann bei starken Formabweichungen nicht garantiert werden. Die primäre Herausforderung liegt vor allem darin, geeignete Zahnradpaarungen zu finden, die trotz der bauteilspezifischen Formabweichungen zur Erfüllung der vorgesehenen Funktion eingesetzt werden können. Da der Trend in Richtung kleinerer Bauteile bei gleichzeitig steigenden Qualitätsanforderungen geht [2], kommt der Qualitätsbeurteilung von Mikrozahnrädern eine immer größere Bedeutung zu. Diese Qualitätsbeurteilung kann einerseits aufgrund der geometrischen Beschaffenheit einzelner Systemkomponenten, andererseits aus dem funktionalen Verhalten des Gesamtsystems erfolgen. An den beiden Instituten IPEK - Institut für Produktentwicklung und wbk - Institut für Produktionstechnik am Karlsruher Institut für Technologie (KIT) wurde in Zusammenarbeit eine Qualitätssicherungsstrategie für Mikroverzahnungen entwickelt, die Aussagen über die Auswirkungen von Gestaltabweichungen auf den Funktionszusammenhang von Mikrozahnrädern ermöglicht. Gefördert wurden diese Arbeiten durch das Schwerpunktprogramm SPP1159 der Deutschen Forschungsgemeinschaft. Als Ergebnis der im Folgenden vorgestellten Arbeiten können Formabweichungen an den Zahnflanken von Mikrozahnrädern derart bestimmt werden, dass eine Auswahl geeigneter Zahnradpaarungen zur Wahrung einer angestrebten Funktionserfüllung möglich ist. Problemstellungen und Lösungsansätze, die im Zusammenhang mit diesen Arbeiten entstanden sind, werden in diesem Artikel dargestellt.

A challenging task for a systematic quality assurance is the characterization of micro gears via metrology. Additional factors in micrometer dimensions such as significant shape deviations of the produced micro gears increase the complexity. This paper describes an approach for a three-dimensional surface characterization of the tooth flanks of micro gears. A three-dimensional point of view defines the functionally relevant tooth flanks as a surface in contrast to the common definition via two-dimensional characteristics. Additionally, this paper describes how these flank characterizations will then be used for matching micro gears afflicted with shape deviations for functioning gearings.

Spatially curved Al-extrusion profiles are often used for lightweight frame structures in vehicle manufacturing. Within the Collaborative Research Centre SFB/Transregio 10, an automated productflexible process chain is established in order to produce and machine such profiles and to join them into frame structures. One of the biggest challenges of this process chain consists in handling, clamping and machining variably formed profiles with precision and without having to change the mechanical system. For this, both the contour of the profile and the position and orientation of the profile during the process have to be determined. In order to have this information provided from inside the process chain, a component-specific scale was developed and realised for the contour detection and precision positioning of multi-dimensionally curved extrusion profiles. The scale is applied onto the surface of the profile by a laser. To determine the contour, the scale is scanned using digital image processing and the profile is measured by a laser triangulation sensor. This establishes the relation between component scale and profile contour. If required, the position of the profile can be readjusted by scanning individual markings again during machining. It is not necessary to re-measure the entire profile contour. The process can be used for different profile contours and profile lengths without having to change the mechanical system. The first section of this article describes the approach for contour detection and precision positioning and its validation for straight profiles, 2D curved profiles and 3D curved profiles with a test rig.

The ubiquitous globalization, which opens up new markets with their specific local conditions and labor costs, as well as the increasing pressure regarding time, costs and flexibility lead to the decentralization of the value added. The resulting global value added networks, consisting of company-owned and external sites as well as logistic partners, have to be configured, operated and optimized. An important criterion for these networks is their ability to a fast and efficient ramp-up. This article presents a concept to assess and select potential value added network’s nodes (sites or external partners) according to their ramp-up performance to achieve an optimal configuration of the network.

Das bereits beschriebene Verfahren des Rundens beim Strangpressen ermöglicht die wirtschaftliche Herstellung räumlich gekrümmter Strangpressprofile und damit die Herstellung leichter Tragwerkstrukturen in kleinen Stückzahlen. Für eine an den Strangpressprozess anschließende Prozesskette zur automatisierten Be- und Weiterverarbeitung der einzelnen Profile zu einer kompletten Rahmenstruktur ist eine flexible und intelligente Greiftechnik zur Handhabung und Bearbeitung der Profile von zentraler Bedeutung. Diese Greiftechnik bildet die Schnittstelle zwischen den einzelnen Prozessen der Gesamtprozesskette. Im folgenden Artikel werden zunächst die aus einer flexiblen Profilbearbeitung und Handhabung heraus resultierenden Anforderungen an eine prozessübergreifende Greiftechnik dargestellt. Darauf aufbauend wird die Vergehensweise zur Ableitung eines Lösungsansatzes am Beispiel der produktflexiblen Bearbeitung räumlich gekrümmter Profile vorgestellt. Im Anschluss an die Ableitung eines Gesamtkonzepts, bestehend aus einer flexiblen Greiftechnik und einer kombinierten Handhabungsund Bearbeitungskinematik, werden die Funktion und der konstruktive Aufbau der entwickelten Greiftechnik, sowie die dazugehörige Greifstrategie beschrieben. Die prototypisch realisierte Greiftechnik ermöglicht das flexible Spannen unterschiedlicher Profile für die spanende Bearbeitung. Anhand der Funktionsbeschreibung und der prototypischen Umsetzung wird aufgezeigt, wie eine produktflexible Anpassung der Greiftechnik an die Profilkontur realisiert wird und somit auf angepasste Vorrichtungen verzichtet werden kann. Außerdem werden die Untersuchungsergebnisse zu unterschiedlichen Messmethoden vorgestellt, die für eine vollständige Bestimmung der Profillage und -Orientierung für die entwickelte Greiftechnik und der dazugehörigen Greifstrategie notwendig sind. Aufbauend auf diesen Untersuchungen wird ein messtechnischer Ansatz vorgestellt, wie die räumliche Profilkontur in Kombination mit bauteileigenen Markierungen inline überwacht werden kann.

Despite continuous improvements in modelling, software tools and data availability, simulation projects of production systems still require a lot of manual effort, exper-tise in various disciplines and time. In many projects the high initial invest for building the simulation model is followed by a rather short period of experimentation and analysis. As pro-duction systems have to be adapted at an increasing pace to respond to rapidly changing markets and business environ-ments, simulation models of these systems become outdated earlier, reducing their useful time window. One way to extend this time window would be the implementation of a method of automated comparison with the current production sys-tems and subsequent self-adaption of the model to reality to maintain and even improve its accuracy over time. This ap-proach will be presented and validated at a real world use case. Such an enhanced simulation model can be called a digital twin of the production system.

Robuste und resiliente Lieferketten (engl. Supply Chain) bilden mehr denn je einen kritischen Erfolgsfaktor für die Wettbewerbsfähigkeit produzierender Unternehmen. Höhere Komplexitäten und steigende Dynamiken in Folge von Megatrends wie der Globalisierung, Nachhaltigkeit und Individualisierung sowie sich häufende Disruptionen stellen heutige Lieferketten dabei auf die Bewährungsprobe. Insbesondere die mittelständisch geprägte Branche der Antriebstechnik im Maschinen- und Anlagenbau mit ihren globalen Lieferketten und hohen Kundenanforderungen steht vor diesen Herausforderungen. Zielgerichtete Digitalisierungsinitiativen sind dabei entscheidend für ihre langfristige Wettbewerbsfähigkeit. Der vorliegende Artikel analysiert daher die gegenwärtigen Digitalisierungsvorhaben der Branche der Antriebstechnik, um relevante Trends und Anwendungsfelder zu identifizieren. Hierzu werden aus dem Zielbild der Branche für höhere Resilienz/Flexibilisierung, höhere Transparenz und mehr Nachhaltigkeit entlang der Supply Chain relevante Handlungsfelder synthetisiert. Diese geben eine fundierte Orientierungshilfe für mittelständische Unternehmen und ihre Digitalisierungsstrategien.

Driven by an increasing demand for individualized products and shorter product life-cycles, companies continuously extend their product portfolio. Simultaneously, companies expand into new markets to reach customers and to exploit varying location factors to reduce costs. Global production networks (GPNs) have to be adapted constantly to react to new circumstances and changes in the demand of products. To remain competitive, product allocation and production network configuration are essential. At the same time, companies face an increasing complexity while handling these tasks. This poses a challenge particularly for small and medium sized companies, which have limited planning capacities and management resources. Current literature describes optimization-based approaches for the integrated product allocation and network configuration of production networks. Yet, multi-objective models lack transparency of results and user friendliness. Therefore, this paper presents a multi-objective optimization model that incorporates flexibility and reconfiguration aspects to determine an optimal product allocation and network configuration of a GPN over a given planning horizon. The preemptive goal programming approach is used to identify Pareto-optimal solutions and to increase user friendliness. The subsequent verification, validation and post-optimality analysis combined in a structured process enables a wide range of companies to apply the approach. The model is successfully applied in the GPN of a special machine manufacturer, which produces high precision metrology machines. Due to its transparent approach for complex planning problems, the developed method provides a solid base for well-founded, objective decisions. Hence, the risk of costly errors in the planning phase is reduced.

As markets demand targeted products for highly diferentiated use cases, the number of variants in production increases, whilst the volume per variant decreases. Diferent product variants result in diferences in work content on workstation level which cause takt time losses and result in a poor utilization. In this context, matrix-structured production systems with neither temporal nor spacial linkage emerged to reduce the efects of diferent work content on the entire production system. However, matrix-structured production systems require far more complex production control. To that end, this paper presents a scheduling approach. The proposed scheduling system considers variable process sequences and their allocation to diferent workstations in order to optimize scheduling objectives. This contribution presents a Monte Carlo tree search based optimizer combined with local search as post optimizer to derive schedules in a short time span to enabling reactive scheduling. The application of the scheduler to a benchmark problem and an industrial scheduling problem demonstrates the quality of the results and illustrates how the scheduler reassigns the work content dynamically

Im Zuge der sich verändernden Produktion wird die Frage essentiell, welche Rolle der Mensch in Zukunft einnehmen wird. Technologien, die auf Künstlicher Intelligenz basieren, nehmen Einzug in die Produktion und verändern damit die Arbeit des Menschen. Aufgaben werden komplexer und Assistenzsysteme können einen Beitrag dazu leisten, den Menschen bei seinen täglichen Aufgaben zu unterstützen. Im Zuge dieses Beitrags wird ein Konzept für die Integration mehrerer KI-basierter Assistenzsysteme entlang einer Montagelinie für Elektromotoren vorgestellt. Anhand dieses Demonstrators sollen die Auswirkungen der Assistenzsysteme auf das sozio-technische Arbeitssystem untersucht werden. Neben der Interaktion von Mensch und KI-System wird zudem die Steuerungsebene betrachtete, um die Messung von prozessseitigen Auswirkungen quantitativ zu bewerten

Competitive remanufacturing of used products with uncertain conditions requires a high degree of flexibility and responsiveness. This article describes an integrated control architecture for a modular, agile disassembly system with autonomous product inspection and learning production resources. The approach includes a material flow control and vertically-integrated sub-architectures to control the station and intralogistics operations.

In der vergangenen Dekade wurden zahlreiche Industrie 4.0-Prototypen entwickelt, die große Erwartungen hinsichtlich des Potentials der Digitalisierung schürten. Es zeigt sich aber, dass aufgrund der fehlenden Skalierung in globalen Produktionsnetzwerken (GPN) diese Erwartungen unerfüllt bleiben. Damit stellt sich die Frage, wie die digitale Transformation in GPN zu gestalten ist. Zu diesem Zweck wurde eine quantitative Studie durchgeführt. Dieser Beitrag präsentiert ausgewählte Ergebnisse zur strategischen und organisatorischen Gestaltung der digitalen Transformation.

Ereignisdiskrete Ablaufsimulationen haben sich als digitales Planungswerkzeug in komplexen Produktionssystemen etabliert und werden zunehmend zu realitätsnahen Digitalen Zwillingen von Produktionssystemen weiterentwickelt. Die langfristig erfolgreiche Nutzung Digitaler Zwillinge in der Produktionsplanung erfordert eine systematische Integration in die bestehende Organisation und Planungsprozesse. Dieser Beitrag präsentiert und erprobt hierfür ein schrittweises Vorgehensmodell, das die Erarbeitung von Nutzergruppen, eines funktionsübergreifenden Interaktionszyklus sowie nutzerorientierter KPI-Visualisierungen unterstützt.

Die Siemens AG in Karlsruhe stellt sich den aktuellen Herausforderungen einer steigenden Produktkomplexität bei höherer Variantenvielfalt mit reduzierter Losgröße und kürzeren Produktlebenszyklen. Für die Umstrukturierung ihres Fertigungssystems zu einer „Matrixproduktion im Fluss“ wurde ein Vorgehensmodell zur Neuplanung und Umstrukturierung entworfen, welches als Leitfaden hierfür dienen soll. Unterstützt durch den Digitalen Zwilling und Simulationsstudien zeigt sich eine optimierte Modulkonfiguration für eine hochflexible Fertigung mit fahrerlosen Transportfahrzeugen. Herausforderungen wie die komplexe Fertigungssteuerung können im Lebenszyklus durch den ganzheitlichen Digitalen Zwilling unterstützt werden.

Eine steigende Variantenvielfalt und Änderungsdynamik bedingen regelmäßige Anpassungen der Produktionssysteme produzierender Unternehmen. Der in diesem Beitrag beschriebene Ansatz eines Lösungsmusters beinhaltet ein schrittweises Vorgehen zur modularen, integrierten Planung von Produktionssystemen. Dabei wird produkt- und produktionsseitiges Wissen in eine einheitlich strukturierte Form überführt und darüber eine Lösung für das Produktionsplanungsproblem abgeleitet.

Remanufacturing includes disassembly and reassembly of used products to save natural resources and reduce emissions. While assembly is widely understood in the field of operations management, disassembly is a rather new problem in production planning and control. The latter faces the challenge of high uncertainty of type, quantity and quality conditions of returned products, leading to high volatility in remanufacturing production systems. Traditionally, disassembly is a manual labor-intensive production step that, thanks to advances in robotics and artificial intelligence, starts to be automated with autonomous workstations. Due to the diverging material flow, the application of production systems with loosely linked stations is particularly suitable and, owing to the risk of condition induced operational failures, the rise of hybrid disassembly systems that combine manual and autonomous workstations can be expected. In contrast to traditional workstations, autonomous workstations can expand their capabilities but suffer from unknown failure rates. For such adverse conditions a condition-based control for hybrid disassembly systems, based on reinforcement learning, alongside a comprehensive modeling approach is presented in this work. The method is applied to a real-world production system. By comparison with a heuristic control approach, the potential of the RL approach can be proven simulatively using two different test cases.

The resilience of globally interconnected production networks to changes in their environment and internal disruptions is an important research object in business and production science. While many different measures to improve resilience have been suggested in academic literature, effectively choosing measures to improve production networks remains challenging. This contribution analyzes measures to improve the resilience of production networks proposed in the existing body of literature. The most commonly suggested measures are discussed in detail. These measures are structured in a conceptual framework to enable increased clarity regarding the mechanics by which measures improve resilience and to choose specific measures for a production network.

Uncoordinated decisions in production networks lead to inefficient structures that endanger a company's competitiveness. To stay competitive in the future, manufacturing companies must focus their production and migrate their production network into agile structures. This paper presents a methodology for migration planning of production networks. First, strategic priorities and capabilities for the production network are formulated. To develop these priorities and capabilities, production resources are identified and combined to desired network configurations. Second, these configurations are transferred into a stochastic- dynamic optimization model to identify a cost-optimal migration strategy. The approach has been validated in the automation industry.

Eine Automatisierung der Inspektion im Remanufacturing bietet die Möglichkeit, Kostenpotenziale zu erschließen. Dies lässt sich mittels robotergeführter optischer Messsysteme erreichen. In diesem Beitrag werden bestehende Ansätze vorgestellt und Herausforderungen für View-Planning-Ansätze diskutiert, welche sich aus den Besonderheiten des Remanufacturing heraus ergeben. Gleichzeitig werden Lösungsansätze für diese Problemstellungen an einem beispielhaften Anwendungsfall aufgezeigt.

The formation of thermally and mechanically induced near-surface microstructures in the form of white layers leads to different hardness properties in these areas. Therefore, this paper conducts systematic surface hardness measurements and uncertainty quantification utilizing the Monte Carlo Method (MCM) in accordance with the Guide to the Expression of Uncertainty in Measurement (GUM). Furthermore, several meta-models describing the hardness course in relationship to the material depth are used to model this nonlinear relationship via machine learning. The evaluation and selection of the optimal model considers the trade-off between measurement uncertainty and prediction quality in terms of mean squared error (MSE). The resulting measurement uncertainty is to be used for the calibration of a non-destructive micromagnetic material sensor. This will then be implemented for in-process monitoring in the outer diameter longitudinal turning process. This should make it possible to detect white layers during machining and to avoid them accordingly by controlling the machine parameters. By means of a soft sensor, the corresponding target value is to be derived from the micromagnetic material sensor measurement.

Manufacturing in the age of Industry 4.0 can be characterised by a high product variety and complex material flows. The increasing individualisation of products requires adaptive production planning and control systems. Research in the area of Machine Learning demonstrates the applicability and potential of Reinforcement Learning (RL) systems for the control of complex manufacturing. However, a major disadvantage of RL-methods is that they are usually considered as "black box" models. For this reason, this paper investigates methods of explainable reinforcement learning in production control. Based on a comprehensive literature review an approach to increase the plausibility of RL-based control strategies is presented. The approach combines the advantages of high prediction accuracy (e.g. neural networks) and high explainability (e.g. decision trees). In doing so, understandable control strategies such as heuristics can be generated, and an advanced RL-system can be designed including specific domain expertise. The results are demonstrated based on a real-world system, taken from semiconductor manufacturing, which is investigated in a simulated approach.

Die zunehmende Digitalisierung der Arbeitswelt stellt Führungskräfte vor neue Herausforderungen. Sie sind gefordert, den Wandel aktiv zu gestalten und dabei die Mitarbeitenden unter sich ständig verändernden Rahmenbedingungen situativ zu führen und zu motivieren. In diesem Fachbeitrag wird die Entwicklung eines Leitbildes vorgestellt, das Führungskräfte unterstützen soll, die notwendigen Rahmenbedingungen für gute Führung und soziale Interaktion in einer digitalisierten Arbeitswelt zu schaffen.

Die adaptive Fertigung von Fertigbetonbauteilen für modulare Tragwerke birgt das Potenzial, Ausschuss und Nacharbeit zu reduzieren. Bei diesem Ansatz wird der Fertigungsprozess auf Basis der Geometrien bereits gefertigter Module iterativ angepasst, sodass sich Maßabweichungen im Gesamttragwerk bestmöglich kompensieren. Im vorliegenden Aufsatz wird untersucht, wie eine solche Kompensation durch gezielte Anordnung der Module in modularen Tragwerken erfolgen kann. Hierzu wird zunächst ein Maß entwickelt, um modulare Tragwerke unter Berücksichtigung der Kompensation von Maßabweichungen geometrisch zu bewerten. Anschließend wird darauf aufbauend ein Optimierungsmodell vorgestellt, mit dem eine optimale Anordnung von Modulen mit gegebenen Maßabweichungen berechnet werden kann. Hiermit werden optimale Lösungen für ausgewählte Fälle betrachtet, um hieraus einen allgemeingültigen Zusammenhang zwischen den Geometrien der einzelnen Bauteile und der geometrischen Bewertung des resultierenden Tragwerks herzustellen. Diese Erkenntnisse dienen als Grundlage für eine adaptive Fertigung.

Modern production systems face enormous challenges due to rising customer requirements resulting in complex production systems. The operational efficiency in the competitive industry is ensured by an adequate production control system that manages all operations in order to optimize key performance indicators. Currently, control systems are mostly based on static and model-based heuristics, requiring significant human domain knowledge and, hence, do not match the dynamic environment of manufacturing companies. Data-driven reinforcement learning (RL) showed compelling results in applications such as board and computer games as well as first production applications. This paper addresses the design of RL to create an adaptive production control system by the real-world example of order dispatching in a complex job shop. As RL algorithms are "black box" approaches, they inherently prohibit a comprehensive understanding. Furthermore, the experience with advanced RL algorithms is still limited to single successful applications, which limits the transferability of results. In this paper, we examine the performance of the state, action, and reward function RL design. When analyzing the results, we identify robust RL designs. This makes RL an advantageous control system for highly dynamic and complex production systems, mainly when domain knowledge is limited.

Currently, manufacturing is characterized by increasing complexity both on the technical and organizational levels. Thus, more complex and intelligent production control methods are developed in order to remain competitive and achieve operational excellence. Operations management described early on the influence among target metrics, such as queuing times, queue length, and production speed. However, accurate predictions of queue lengths have long been overlooked as a means to better understanding manufacturing systems. In order to provide queue length forecasts, this paper introduced a methodology to identify queue lengths in retrospect based on transitional data, as well as a comparison of easy-to-deploy machine learning-based queue forecasting models. Forecasting, based on static data sets, as well as time series models can be shown to be successfully applied in an exemplary semiconductor case study. The main findings concluded that accurate queue length prediction, even with minimal available data, is feasible by applying a variety of techniques, which can enable further research and predictions.

Inspektionsprozesse werden im Remanufacturing auch heute noch vorwiegend manuell durchgeführt, da die Einschätzung des Qualitätszustands von rückläufigen Gebrauchtprodukten komplex und damit schwer zu automatisieren ist. Dies ist darauf zurückzuführen, dass Abnutzungsgrade, Deformationen und Schädigungen eine individuelle Bewertung des Gebrauchtprodukts nach sich ziehen und somit schwer standardisierbar sind. In diesem Beitrag werden die Anforderungen an ein System für die Bewältigung der Herausforderung der automatisierten Inspektion im Remanufacturing abgeleitet. Darauf aufbauend wird das Konzept einer Befundungsstation, welches diese Anforderungen erfüllt, präsentiert und Anwendungsfälle im Rahmen des von der CarlZeiss-Stiftung geförderten Forschungsprojekts „AgiProbot - Agiles Produktionssystem mittels mobiler, lernender Roboter mit Multisensorik bei ungewissen Produktspezifikationen“ vorgestellt.

Eine steigende Variantenvielfalt, hohe Marktvolatilität und heterogene Prozesslandschaften betonen die Bedeutung einer simultanen Betrachtung von Produkt- und Produktionssystem für produzierende Unternehmen. Vor dem Hintergrund einer wandlungsfähigen Produktionsplanung und -steuerung stellt dieser Beitrag eine Methodik zur Implementierung eines integrierten Produkt-Produktions-Codesign vor. Bestandteile sind ein ganzheitliches Änderungsmanagement und die Identifikation von Lösungsmustern.

Das Remanufacturing, bisher geprägt durch manuelle und kostenintensive Prozesse, ist ein entscheidender Schritt auf dem Weg zu einer ressourcenschonenden Kreislaufwirtschaft. Industrie und Forschung sind sich einig, dass der Einzug von Industrie 4.0 Technologien den Schlüssel zu einer Entwicklung automatisierter und wirtschaftlicher Remanufacturing-Systeme darstellt. Basierend auf einer systematischen Literaturrecherche widmet sich dieser Beitrag der Analyse vielversprechender Industrie 4.0-Ansätze mit dem Fokus auf den übergeordneten Gesamtprozess sowie den Teilprozessen der Demontage und der Inspektion. Die Ergebnisse legen nahe, dass es an zusätzlichem Wissen, Erfahrung und Forschung bei der Entwicklung und realen Demonstration der Ansätze und deren Übertragbarkeit auf breitere Anwendungsfelder bedarf.

Trotz der Vielzahl von verschiedensten Anwendungen und Anforderungen an die Batteriezellen werden für viele Produkte standardisierte Zellen eingesetzt. Dabei werden individuelle Anforderungen, insbesondere an den Bauraum, meist nicht beachtet. Unsere Hypothese ist, dass künftige Produkte, vor allem in den Bereichen Unterhaltungselektronik, Power Tools und Elektrofahrzeuge, Batteriezellen benötigen, deren Anforderungen bezüglich elektrischer Eigenschaften und Format angepasst sind. Dies führt zu einer wachsenden Vielfalt an Batteriezellen in Bezug auf Abmessungen, Format und Materialien. Dieser Trend ist bereits bei Batteriezellen für die Unterhaltungselektronik wie Smartwatches und Smartphones erkennbar. Um den unterschiedlichen Kundenanforderungen gerecht zu werden, benötigen die Zellhersteller geeignete flexible Produktionsmaschinen, um hohe Rüstkosten zu vermeiden. Als Lösung wird am KIT eine flexible, automatisierte Produktionsanlage für die Li-Ionen Pouch-Zellen Fertigung entwickelt.

In diesem Beitrag wird eine Methode vorgestellt, die ausgehend vom Mischgraphen unter Berücksichtigung der minimalen Auslastung der Stationen und benötigter Betriebsmittel eine variantenflexible Allokation der Arbeits inhalte auf die Produktionsstationen ermittelt. Ziel ist eine Allokation auf die Stationen der Mehrproduktlinie zu wählen, bei der stations weise eine minimale Auslastung erreicht wird und der Korridor, innerhalb dessen die Variantenanteile schwanken dürfen, maximal ist.

The trend of globalization has led to a structural change in the sales and procurement markets of manufacturing companies in recent decades. In order not to be left behind by this change, companies have internationalized their production structures. Global production networks with diverse supply and service interdependencies are the result. However, the management of global production networks is highly complex. Key performance indicator (KPI) networks already exist at the corporate level and site level to support the management of complex systems. However, such KPI networks are not yet available to support the management of entire production networks. In this article, a KPI network for global production networks is presented, which links the key figures of the site level and the corporate level. By integrating both levels into a comprehensive KPI network, cause and effect relationship between the production-related KPIs and the strategic KPIs of a corporate strategy become transparent. To this end, this KPI network is integrated into a Performance Measurement and Management (PMM) methodology. This methodology consists of three phases: performance planning, performance improvement, and performance review. For testing the practical suitability, the PMM methodology is applied to the production network of an automotive supplier using a simulation model to estimate the effects of proposed improvement actions of the methodology.

Given today's demand shift for product variants triggered by different market segments, manufacturing companies are facing high degrees of complexity, when utilising their global production networks. To remain competitive, companies need to prepare proactively for increasing demand dynamics by using the adaptability of their production network and planning their product allocation to production network entities comprehensively. In this paper, a mixed-integer linear program (MILP) is proposed for the integrated product variant allocation and configuration adaption of global production networks. Further improvement potential for the optimal solution is identified and evaluated by means of post-optimality analysis, i.e. an analysis of shadow prices and slack variables is conducted. This approach contributes towards decision-making in the context of strategic production network design. Its application may reduce the risk of disadvantages decisions and supports the identification of further improvement measures in complex decision-making problems while improving decision transparency. The approach is applied at a global production network for final assembly in the aeronautics industry.

Bedingt durch volatile und neue Rahmenbedingen wird es für Unternehmen wichtiger, ihre Wettbewerbsfähigkeit durch den effizienten Einsatz ihrer Ressourcen im globalen Produktionsnetzwerk abzusichern und verschiedene denkbare Entwicklungen zu berücksichtigen. Hierzu wird ein Verfahren entwickelt, das dies für ein Problem der integrierten Auftragsallokation und Netzwerkkonfiguration ermöglicht. Die Berücksichtigung von Auftragsunsicherheit im entwickelten Verfahren ist heuristisch und basiert auf einer Prognose zukünftig denkbarer Szenarien. Aufbauend auf den szenariospezifischen Lösungen eines linearen Optimierungssystems werden Entscheidungen identifiziert, die die Robustheit der Planung steigern. Diese Entscheidungen werden fixiert und in einem Anwendungsfall bezüglich der ursprünglichen, nicht robusten Planung in verschiedenen Szenarien bewertet.

Low information exchange in global production networks results in long response time to disruption and negative performance impact. Digitalization enables a more intensive information exchange. This paper analyses the performance of order management, quality problem resolution and engineering change management in production networks with respect to different disruptions and information flows. Causeeffect relationships are revealed based on a multi-method simulation model and statistical experiments. Using surrogate modelling and robust optimization, a target picture for information exchange is determined. The benefits of the approach are demonstrated using a case study for the production of metal-plastic parts for the automotive supplier industry.

Bauen im Regen, eine katastrophale Vorstellung, doch Praxis auf Baustellen. Es bringt Ungenauigkeit, behindert den Einsatz moderner Hochleistungswerkstoffe und kostet Zeit, da Störungen im Bauprozess oft umständliche Rückläufe in den Planungsprozess bedeuten. Dennoch gilt der handwerklich geprägte Bauprozess als unvermeidlich, da jedes Bauwerk individuell und in Handarbeit vor Ort zu erstellen ist. Tatsächlich? Das von der Deutschen Forschungsgemeinschaft eingerichtete Schwerpunktprogramm "Adaptive Modulbauweisen mit Fließfertigungsmethoden" setzt auf einen gänzlich neuen Ansatz. Baustrukturen werden in ähnliche modulare Betonfertigteile zerlegt, in Serienfertigung mit Fließprinzip vorgefertigt, in ihrer Qualität gesichert und auf der Baustelle nur noch zusammengefügt. Die Bauzeiten reduzieren sich auf wenige Tage oder Wochen. Vergleichbar einem Puzzle aus vielen Teilen, bleibt die Einzigartigkeit des Tragwerks erhalten. Es gilt: "Individualität im Großen - Ähnlichkeit im Kleinen". Der Beitrag zeigt Ansätze zur Modularisierung, Produktionskonzepte und verknüpfende digitale Modelle. Durch die ortsfeste Vorfertigung in Serie entstehen hohe Produktionsgeschwindigkeiten und schlanke, ressourceneffiziente Module, die zu Tragwerken mit geringen Maßabweichungen assembliert werden. Eine durchgängige Digitalisierung sichert die Qualität aller Einzelschritte. Sie reicht von der Fertigung über den Zusammenbau bis in die Nutzungszeit des Tragwerks. Es entsteht ein verschwendungsarmer, ressourceneffizienter Gesamtprozess.

During turning of quenched and tempered AISI4140 surface layer states can be generated, which degrade the lifetime of manufactured parts. Such states may be brittle rehardened layers or tensile residual stresses. A soft sensor concept is presented in this work, in order to identify relevant surface modifications during machining. A crucial part of this concept is the measurement of magnetic characteristics by means of the 3MA-testing (Micromagnetic Multiparameter Microstructure and Stress Analysis). Those measurements correlate with the microstructure of the material, only take a few seconds and can be processed on the machine. This enables a continuous workpiece quality control during machining. However specific problems come with the distant measurement of thin surface layers, which are analyzed here. Furthermore the scope of this work is the in-process-measurement of the tool wear, which is an important input parameter of the thermomechanical surface load. The availability of the current tool wear is to be used for the adaption of the process parameters in order to avoid detrimental surface states. This enables new approaches for a workpiece focused process control, which is of high importance considering the goals of Industry 4.0.

Beschleunigte Produktentwicklungs- und Anpassungszyklen sowie zunehmende Variantenvielfalt veranlassen Unternehmen flexiblere, mitarbeitergebundene Produktionssysteme einzuführen. Die Analyse der komplexen Wechselwirkungen zwischen den Aktionen mehrerer Mitarbeiter innerhalb solcher Systeme kann mit einer Ablaufsimulation erfolgen. Um die Erstellung solcher Simulationsmodelle zu vereinfachen, wurde ein generisches Modellierungskonzept entwickelt, das es erlaubt, durch ereignisdiskrete Materialflusselemente mit agentenbasierten Mitarbeitern solche komplexen Strukturen abzubilden. Der vorliegende Beitrag zeigt die M?glichkeiten für einen beschleunigten Aufbau eines Simulationsmodells zur Bewertung von Verbesserungsmaßnahmen in variablen halbautomatisierten Produktionssystemen.

Die Kreislaufwirtschaft als Konzept zur nachhaltigen Produktion weist eine stetig steigende Relevanz auf. Gleichzeitig stellt deren Umsetzung für Unternehmen häufig eine große Herausforderung dar und erfordert branchen- und produktspezifische Lösungen. Ziel dieses Beitrags ist die Schaffung eines Rahmenmodells für Anforderungen und Charakteristika einer kreislauffähigen Produktion, sowie die Analyse von Konzepten, welche einen Wandel zu zirkulären Geschäftsprozessen ermöglichen.

This paper presents a framework to utilize multivariate time series data to automatically identify reoccurring events, e.g., resembling failure patterns in real-world manufacturing data by combining selected data mining techniques. The use case revolves around the auxiliary polymer manufacturing process of drying and feeding plastic granulate to extrusion or injection molding machines. The overall framework presented in this paper includes a comparison of two different approaches towards the identification of unique patterns in the real-world industrial data set. The first approach uses a subsequent heuristic segmentation and clustering approach, the second branch features a collaborative method with a built-in time dependency structure at its core (TICC). Both alternatives have been facilitated by a standard principle component analysis PCA (feature fusion) and a hyperparameter optimization (TPE) approach. The performance of the corresponding approaches was evaluated through established and commonly accepted metrics in the field of (unsupervised) machine learning. The results suggest the existence of several common failure sources (patterns) for the machine. Insights such as these automatically detected events can be harnessed to develop an advanced monitoring method to predict upcoming failures, ultimately reducing unplanned machine downtime in the future.

Currently, the laser powder bed fusion (L-PBF) process cannot offer a reproducible and predefined quality of the processed parts. Recent research on process monitoring focuses strongly on integrated optical measurement technology. Besides optical sensors, acoustic sensors also seem promising. Previous studies have shown the potential of analyzing structure-borne and air-borne acoustic emissions in laser welding. Only a few works evaluate the potential that lies in the usage during the L-PBF process. This work shows how the approach to structure-borne acoustic process monitoring can be elaborated by correlating acoustic signals to statistical values indicating part quality. Density measurements according to Archimedes? principle are used to label the layer-based acoustic data and to measure the quality. The data set is then treated as a classification problem while investigating the applicability of existing artificial neural network algorithms to match acoustic data with density measurements. Furthermore, this work investigates the transferability of the approach to more complex specimens.

The economically successful implementation of Industry 4.0 methods in industrialcompanies requires a structured introduction process. The main objective of such astructured implementation process is the case-specific analysis and evaluation ofavailable Industry 4.0 methods to select the most suitable ones for an individualcompany. The presented methodology aims to establish a financial, strategic, andbenefit-oriented evaluation approach for Industry 4.0 methods to assess their potential.The core of our methodology is a general Industry 4.0 toolbox providing a structuredclassification of different methods. In the first phase, a limited set of Industry 4.0methods is derived from the toolbox by classification into production typologies. In thesecond phase, all Industry 4.0 methods of the derived set are strategically assessed aswell as evaluated from a monetary perspective. The evaluation of the methods isbased on company-specific characteristics, its strategic focus, and its (market)environment. Based on this evaluation, we develop specific, value-addingimplementation scenarios. In the third phase, the identified implementation scenarioswith their specific order of prioritized methods are simulated in a System Dynamicsmodel. The three phases ultimately result in a recommendation for a company-specificIndustry 4.0 implementation roadmap

Competitive production planning has to enable the realization of customer requirements regarding order configurations and lead times. In case short lead times are required, medium-term planning must take place when customer orders have not been received yet. In the short-term, robustness can be achieved by minimizing the impact of adapting the medium-term plan according to incoming customer orders. Thus, disturbances in the production network and its supply chain can be avoided. Therefore, an order planning approach is proposed providing continuity between medium-term and short-term planning as well as integrating the intra-organisational supply chain with its interface to the suppliers. The approach covers three planning tasks: the medium-term generation of planned orders anticipating customer orders, their medium-term assignment to production locations of the production network as well as the medium-to short-term assignment of incoming customer orders to planned orders. An industrial application is presented for an automobile manufacturer considering the documentation of its multi-variant products. Simulation is used to validate the robustness of the assignment of incoming customer orders to planned orders assigned in the production network. The managerial implication is that robustness of planning and a reliable confirmation of delivery times can be achieved by planning with orders in the medium-term and utilizing different types of reconfiguration flexibility in the short-term.

Die Technologien von Industrie 4.0 bieten global produzierenden Unternehmen die Chance, Entscheidungen zur Netzwerkgestaltung zu verbessern und die Steuerung der Produktion weltweit zu synchronisieren. Dadurch werden eine nachhaltige Steigerung des Wertschöpfungsgrads in der Produktion und die Nutzung von Kostenvorteilen ermöglicht. In der Praxis zeigt sich jedoch, dass die Umsetzung ein langer Weg ist. Durch die Unterteilung der Vision eines transparenten und agilen Netzwerks in gestaffelte und parallelisierte Teilprojekte lässt sich jedoch auf allen Arbeitsebenen direkter Mehrwert für Mitarbeiter und Unternehmen erzielen, der gleichzeitig zur Gesamtentwicklung beiträgt. Der vorliegende Beitrag zeigt hierzu konkrete Schritte aus den Bereichen Strategie, Gestaltung und Management von Produktionsnetzwerken auf.

Zum Erreichen einer minimalen Messunsicherheit ist es in der industriellen Computertomographie (CT) nötig, der Messaufgabe angemessene Einstellungen zu wählen. Aufgrund der vielfältigen Einstellmöglichkeiten müssen die richtigen Einstellungen langwierig durch systematische Variation ermittelt werden. Dieser Artikel schlägt unter Berücksichtigung der CT-spezifischen Eigenheiten ein Vorgehen vor, wie solche Unsicherheitsstudien mit einem möglichst geringen Aufwand realisiert werden können.

Um in der Großserienfertigung Carbonfaser-Preforms bewerten zu können, ist eine prozessintegrierte Defektdetektion nötig. Hierbei ist eine Messtechnik zu wählen, die zum einen die Erfassung von Defekten in 3D ermöglicht und zum anderen mit den Eigenschaften des Materials und dem Bauteil zurechtkommt. Die vorgestellte Messstation des Karlsruher Instituts für Technologie bietet durch die Kombination von zwei Laserlichtschnittsystemen sowie durch die Höhennachführung der Sensorsysteme die Möglichkeit, komplexe Geometrien zu erfassen.

Baden-Württemberg und der Suzhou Industrial Park gelten als innovative und wirtschaftsstarke Gebiete in Deutschland bzw. in China. Kooperationen zwischen dort ansässigen Unternehmen bieten daher vielversprechende Synergiepotentiale. Durch leitfadenorientierte Interviews mit 25 Experten aus Baden-Württemberg und der Provinz Jiangsu wurden industrielle Synergien identifiziert. Enge Kooperationen werden vor allem von chinesischen Unternehmen angestrebt, um in China in den Wachstumsfeldern Automatisierungstechnik und Umwelttechnik gemeinsame Lösungen anbieten zu können.

Eng verknüpft mit der Entwicklung zur Industrie 4.0 steht der Begriff Smart Factory. Die nächste industrielle Revolution bietet jedoch nicht nur Potenziale in Bezug auf den Einzelstandort, sondern auch für die effiziente Vernetzung von Standorten zu einem Smart Network. Entsprechend ist Industrie 4.0 in der Lage, einen wichtigen Beitrag zum Management globaler Produktionsnetzwerke zu leisten. Im vorliegenden Beitrag wird erläutert, welchen Einfluss Industrie 4.0 auf das strategische Management, die Gestaltung und die Steuerung von Produktionsnetzwerken haben kann. Dabei wird insbesondere aufgezeigt, welche Voraussetzungen auf dem Weg zu Smart Networks zu schaffen sind und inwieweit die Leistungsfähigkeit von Produktionsnetzwerken dadurch positiv beeinflusst wird.

In frühen Phasen der Produktentstehung sind Informationen häufig mit Unsicherheiten behaftet, dies gilt auch für unreife Technologien im Bereich der Elektromobilität. Der Fachbeitrag stellt ein stochastisches Modell zur Prognose von Produktionskosten vor, das sowohl unsichere Informationen einbezieht als auch Korrelationen zwischen verschiedenen Kostenarten berücksichtigt. Das Modell basiert auf den Grundsätzen der Monte-Carlo-Simulation und passt sich flexibel der gegebenen Datengrundlage an.

Für die prozessintegrierte Regelung von Fertigungsprozessen steht eine Vielzahl von Messverfahren zur Verfügung. Ein möglicher Ansatz ist die “In-situ”-Integration der Messtechnik in der Werkzeugmaschine. Dies verkürzt den Informationsaustausch zwischen der Messung und der Fertigung und reduziert die Nebenzeiten des Prozesses. Das Ziel der vorliegenden Untersuchungen war, ein “In-situ”-Integrationskonzept am Beispiel einer Getriebefertigung monetär zu bewerten. Die Ergebnisse der Kostenanalyse zeigen, dass der Einsatz des “In-situ”-Integrationskonzepts in unterschiedlichen Szenarien innerhalb der Fertigung zu monetären Vorteilen führen kann.

Das Marktumfeld der Elektromobilität ist durch Marktunsicherheit und -dynamik geprägt. Vor allem in den frühen Phasen der Produktentstehung sind Herstellkostenprognosen mit einem hohen Grad an Unsicherheit verbunden. Im vorliegenden Beitrag werden deshalb die Konzeptionierung und die Anwendung eines stochastischen Prognosemodells vorgestellt, um bereits zu einem sehr frühen Zeitpunkt eine Kostenabschätzung für die Produktherstellung durchführen zu können.

Da Verbindungszonen in Hybridverbunden unter einer erhöhten Belastung stehen, ist hier insbesondere auch die Auswirkung von Defekten in der Fügezone auf die mechanischen Kennwerte zu untersuchen. Neben dieser Untersuchung im ausgehärteten Bauteil müssen Konzepte zur frühzeitigen prozessintegrierten Detektion von Imperfektionen im Lagenaufbau des textilen Halbzeugs erarbeitet werden. Hierbei werden die Fragestellungen von den Projektpartnern der TU Dortmund, des Karlsruher Institut für Technologie (KIT) und der Universität des Saarlandes gemeinschaftlich betrachtet.

Deutschland ist das am stärksten industrialisierte Land der EU. Die enge Zusammenarbeit zwischen Wirtschaft und Wissenschaft sichert einen schnellen Markteintritt neuer Technologien. Die Produktion hat dabei stets einen integrativen Charakter als "Enabler" von Disziplinen bei der Umsetzung einer Idee in ein Produkt. Um den wachsenden Herausforderungen am Hochlohnstandort gerecht zu werden, müssen immer wieder sämtliche Potenziale neuer Technologien gehoben werden. Aktuell ist die Informations- und Kommunikationstechnologie ein besonders prominenter "Enabler" des "Enablers".

Bestehende Servicenetzwerke lassen sich hinsichtlich des Bedarfs monetärer, menschlicher und materieller Ressourcen optimieren. Bei einer Neugestaltung des Servicenetzwerkes sind sowohl die Anordnung des Netzwerkes selbst bestehend aus Standorten und Kunden als auch die Auswahl der Servicestrategiekombinationen, d. h. der Beschaffungs-, Lagerhaltungs- und Instandhaltungsstrategien, ein wesentlicher Effizienzfaktor. Im Rahmen eines DFG Forschungsvorhabens*) wurden für die Auswahl der Strategiekombinationen ganzheitliche Entscheidungsmatrizen entwickelt.

Manufacturing companies are continuously facing the challenge of operating their manufacturing processes and systems in order to deliver the required production rates of high quality products, while minimizing the use of resources. Production quality is proposed in this paper as a new paradigm aiming at going beyond traditional six-sigma approaches. This new paradigm is extremely relevant in Technology intensive and emerging strategic manufacturing sectors, such as aeronautics, automotive, energy, medical technology, micro-manufacturing, electronics and mechatronics. Traditional six-sigma techniques show strong limitations in highly changeable production contexts, characterized by small batch productions, customized, or even one-of-a-kind products, and in-line product inspections. Innovative and integrated quality, production logistics and maintenance design, management and control methods as well as advanced technological enablers have a key role to achieve the Overall production quality goal. This paper revises problems, methods and tools to support this paradigm and highlights the main challenges and opportunities for manufacturing industries in this context.

In the last three decades, companies have intensified their global business activities with suppliers and thereby were able to focus on their core competencies. Today, supplier development in low cost countries is of increasing strategic importance due to its high cost-cutting potential; however, especially low cost country sourcing features high decision complexity and challenges due to changing corporate environment. This paper presents a three step approach to include uncertainty and flexibility into the decision making process on supplier development, using real options valuation. First, the procurement object is analysed followed by an analysis of the corporate environment in which dynamic environmental factors and risks are evaluated. In the final step, the real options value of the supplier development project is determined, including market risks and flexibility of action. The methodology of real options valuation is a useful tool for supplier evaluation in a low cost country environment since it provides a gradual increase in prediction quality through a project accompanying evaluation and therefore allows for more reliable planning.

Globale Wertschöpfungsnetzwerke gewinnen für die Produktion zunehmend an Bedeutung. Um unter Bedingungen großer Sprach-, System- und Kulturvielfalt eine hohe Produktqualität zu gewährleisten, muss die Qualitätssicherung standort- und unternehmensübergreifend gestaltet werden. Ein Forschungsprojekt entwickelte Methoden, mit denen Unternehmen für ihr spezifisches Wertschöpfungsnetzwerk die optimale Qualitätssicherungsstrategie finden.

Batterien, Leichtbauteile und Mikrostrukturen werden nach neuen Produktionstechnologien gefertigt. Dies erfordert auch eine auf den Prozess abgestimmte Fertigungsmesstechnik. Dabei zeichnen sich drei Trends ab.

Bei der Herstellung von hochbelastbaren CFK-Bauteilen werden die Teilprozesse im RTM-Verfahren durch die Stückzahl und das Zielsegment bestimmt. Davon wird maßgeblich die Vorgehensweise für das Preforming beeinflusst. Der hier durchzuführende Formgebungsprozess stellt mit der Qualitätssicherung die größte Herausforderung dar. Um eine wirtschaftliche Fertigung zu realisieren muss eine geeignete Vorgehensweise ausgewählt werden.

Leichte Tragwerkstrukturen auf Basis von Aluminiumstrangpressprofilen zeichnen sich durch ihr geringes Gewicht und ihren modularen Aufbau aus. Aus diesem Grund werden sie häufig bei Fahrzeugen in Kleinserien eingesetzt. Zur automatisierten und wirtschaftlichen Montage solcher Strukturen wurden am wbk Institut für Produktionstechnik zwei neue Ansätze entwickelt und im Einzelnen erprobt, wobei die Reduktion von Ausschuss und der weitest gehende Verzicht von kostenintensiven Vorrichtungen während der Montage im Vordergrund stehen. Mit den Ansätzen ist es einerseits möglich vor dem Beginn der Montage Abweichungen zu erkennen, und durch entsprechende Maßnahmen zu kompensieren. Anderseits wurde ein Verfahren entwickelt, das es ermöglicht, die Fügepartner weitgehend vorrichtungsfrei in ihrer Soll-Lage und Orientierung anzuordnen. Aktuelle Arbeiten beschäftigen sich mit der Integration dieser beiden Verfahren in eine prototypische Prozesskette. Zu diesem Zweck wird ein flexibler Montagegreifer für gerundete Strangpressprofile entwickelt und prototypisch realisiert.

Die Qualität der eigenen Produkte steht und fällt mit der Qualität der Zulieferkomponenten. Beschafft wird heute weltweit und insbesondere in Niedriglohnländern. Eine ganzheitliche Methodik, die softwaregestützt hilft, strategische Entscheidungen beim Global Sourcing zu treffen, wurde jetzt gemeinsam mit vier Praxispartnern am Karlsruher Institut für Technologie entwickelt.

Der wirtschaftliche Umgang mit der Volatilität der Absatzmärkte ist heute eine der zentralen Herausforderungen der Investitions- und Kapazitätsplanung in der Produktion. Die Krise der vergangenen Jahre ist dafür ein besonders extremes Beispiel. Mit Hilfe eines in einem Softwaredemonstrator umgesetzten Optimierungsverfahrens konnten bei einem mittelständischen Automobilzulieferer optimale Strategien als Entscheidungsunterstützung für volatile Märkte abgeleitet werden.

Das Angebot technischer Services im Bereich der Wartung und Instandhaltung von Maschinen und Anlagen wird durch die stetige Ausweitung von Produktions- und Verkaufsnetzwerken immer komplexer. Gerade Dienstleistungen, wie die Ersatzteilbereitstellung und die Übernahme von konkreten Instandhaltungsinhalten, stellen vor Allem für klein- und mittelständische Unternehmen des Maschinen- und Anlagenbaus in Deutschland ein großes wirtschaftliches Potential dar. Eine Steigerung des Nutzens und damit auch eine Steigerung der Gewinne für die Anbieter sind jedoch nur erzielbar, falls der Kostenaufwand über die gesamte Laufzeit vor der Angebotsabgabe kalkuliert werden kann. Vor diesem Hintergrund war das Ziel des Forschungsvorhabens WiTal (Wissenstransfer und Grundlagenbereitung technischer Dienstleistungen im Maschinen- und Anlagenbau), welches durch die Stiftung Baden-Württemberg finanziert und durch den Projektträger im Deutschen Zentrum für Luft- und Raumfahrt betreut wurde, insbesondere klein- und mittelständische Unternehmen zu befähigen, technische Dienstleistungen systematisch zu entwickeln und wirtschaftlich umzusetzen.

Since the 1990s a transition from mass production systems to integrated production systems has been taking place. Realising the potential of integrated production systems to reduce costs by avoiding waste, more and more companies follow the example of Toyota and try to increase their production systems’ performance by applying lean elements and methods. However, the lack of a holistic methodology to forecast the profitability of the application of lean elements and methods impedes the justification of necessary investments. This paper presents an approach developed at the Institute of Production Science (wbk) of the Karlsruhe Institute of Technology (KIT) to valuate the increased performance of a production system by lean elements and methods. By simulating and optimising the analysed production system, the ideal combination of lean methods can be identified. Key performance indicators of the real and ideal states of the production system can then be used to quantify the effects of the ideal combination of lean methods.

Zur Simulation des Qualitätssicherungsverhaltens von Unternehmen in Wertschöpfungsnetzwerken wurde am wbk Institut für Produktionstechnik ein agentenbasiertes Entscheidungsunterstützungssystem entwickelt. Das System basiert auf qualitätssicherungsspezifischen Teilmodellen für Produkte, Unternehmen, die Kunden-Lieferanten-Beziehung sowie Wertschöpfungsnetzwerke. Die Implementierung erfolgte auf Basis der Simulationsplattform SeSAm. Erste Versuche bestätigen die erfolgreiche Abbildung des dezentralen Entscheidungsverhaltens, das als entscheidende Eigenschaft zur Beschreibung des Verhaltens realer Netzwerke betrachtet wird.

Economic globalization leads to ever-growing pressure on the competitive strength of companies at the global level. Consequently, the ability to transfer innovative technologies to production companies is crucial. The wbk Institute of Production Science at the Karlsruhe Institute of Technology KIT is concentrating on research and the translation of the findings into innovative solutions for production companies. Our main activities are focused on education and application oriented research within the three departments Manufacturing and Materials Technology, Machine Tools and Handling Technology and Production Systems, (presided by Prof. Dr.-Ing. habil. Volker Schulze, Prof. Dr.-Ing. Jürgen Fleischer and Prof. Dr.-Ing. Gisela Lanza, who represent the board of management). The Manufacturing and Materials Technology department is dedicated to the investigation of interdependencies within the machining processes of industrial materials. The goal of the Machine Tools and Handling Technology department is to develop innovative, integrated solutions for machine tools, as well as the process near, process distant and process-overlapping handling technology. One example is the collaborative research centre SFB/TR10, which looks into developing and transforming a process chain for the flexible production and machining of spatially curved extrusion profiles (see Figure 1). Furthermore, the Production Systems department is not limited to improving the performance of individual production processes, but also includes the monitoring and optimisation of complete production networks. Beyond the technology region of Karlsruhe, we also cooperate with industrial partners aiming to find solutions to diverse problems within the field of production technology and to develop new methods and processes for tomorrow´s production environment.

Chinesische Lieferanten erfüllen nicht immer auf Anhieb die Erwartungen des Einkaufs hierzulande. Das gilt insbesondere für Qualität, Umweltschutz und Arbeitssicherheit. Unsere Autoren berichten hier von einem Projekt, welches die Produktionsbedingungen und das Produktionsumfeld im Ursprung, nämlich beim Lieferanten, nachhaltig verbessern soll.

Die Montage von leichten Rahmenstrukturen erfolgt bei kleinen Stückzahlen in der Regel manuell. Die Möglichkeit zur Verbesserung der Wirtschaftlichkeit sowie zur Steigerung der Reproduzierbarkeit der Qualität sprechen jedoch für eine automatisierte Montage in der Kleinserie. Da bei kleinen Stückzahlen Prozesse meist nicht eingefahren werden können, entstehen Abweichungen an den einzelnen Bauteilen. Der Umgang mit Abweichungen und eine exakte, vorrichtungsfreie und damit flexible Positionierung der Bauteile bei der Montage stellt daher eine große Herausforderung dar. Am wbk Institut für Produktionstechnik wird ein Ansatz zur vorrichtungsfreien und flexiblen Montage von Rahmenstrukturen mit Industrierobotern verfolgt. Dazu wird eine Methodik entwickelt, mit welcher fertigungsbedingte Abweichungen ausgeglichen werden, und die Bauteile vorrichtungsfrei präzise zueinander positioniert werden können.

Die vorgestellte Unternehmenskurzstudie zeigt, in welcher Implementierungsstufe sich Unternehmen bei der Einführung von Lean-Methoden derzeit befinden, welche Methoden sie vorzugsweise einsetzen und welchen Anteil diese zur Erreichung angestrebter Ziele beitragen. Zusätzlich werden vermisste Hilfestellungen während der Einführung und mögliche Ausprägungsstufen der verbreiteten Methoden vorgestellt.

Unsere Mobilität ist in hohem Maße von fossilen Brennstoffen abhängig. Die Beschränktheit dieser Ressourcen, die negativen Auswirkungen auf den Menschen und seine Umwelt durch deren Verbrennung sowie verschärfte gesetzliche Regulierungen führen seit Jahren zu massiven Anstrengungen in Wissenschaft und Wirtschaft alternative Mobilitätskonzepte insbesondere für den automobilen Individualverkehr zu entwickeln. Der damit verbundene Strukturwandel innerhalb und außerhalb der Produktionswerke der Automobilhersteller wird zukünftig stärker in den Fokus rücken. Im Folgenden wird ein Überblick über produk-tionstechnische Herausforderungen gegeben sowie mögliche Lösungsideen und Thesen diskutiert.

Kleine und mittlere Unternehmen (KMU) beschäftigen üblicherweise keine Stabsstellen oder Planungsexperten zur Auslegung von Lean-Systemen. Außerdem verfügen die Mitarbeiter in KMU im Allgemeinen nicht über notwendige Erfahrung, um eine Lean-Planung ohne unterstützende Hilfsmittel schnell und zielgerichtet durchzuführen. Aus diesem Grund wurde im Projekt HyPlan ein hybrides Planungswerkzeug zur adaptiven Auslegung von Lean-Methoden in der variantenreichen Kleinserienproduktion entwickelt und prototypisch realisiert. Dieses Planungswerkzeug leitet den Planer schrittweise und systematisch durch den Planungsprozess und unterstützt ihn bei der Auswahl und Auslegung der Methoden des Lean-Systems.

Die globale Verflechtung der Produktion führt zu einer hohen Dynamik des wirtschaftlichen Handelns. Mehr noch als bisher müssen Produktionsplaner Unsicherheiten und plötzlich auftretende Schwankungen bei langfristigen Planungen berücksichtigen. Dabei muss der Betrachtungsfokus so gefasst werden, dass die Möglichkeiten und Anforderungen einzelner Werke als Teil eines Verbundes im Netzwerk erfasst und berücksichtigt werden.

Der VDI-Fachausschuss „Fabrikplanung“ befasst sich als Gremium der VDI-Gesellschaft „Produktion und Logistik“ mit der Erarbeitung fabrikplanerischer Themen, die im Hinblick auf den Wissenstransfer in die verarbeitende Industrie anwendungsorientiert aufbereitet werden. Als ein wesentliches Ergebnis der Fachausschussaktivitäten der vergangenen Jahre ist 2009 die VDI-Richtlinie „Fabrikplanung“ (5200) entstanden. Um in dem zunehmend turbulenten und globalen Umfeld Zukunftsthemen der Fabrikplanung zu identifizieren, wurde eine Umfrage unter VDI-Mitgliedern durchgeführt. Die vorliegende Veröffentlichung gibt die zentralen Ergebnisse der Umfrage wieder.

Die zunehmende Vernetzung der Wirtschaftsräume im Zuge der fortschreitenden Globalisierung ermöglicht heute weltweite Beschaffungs-, Fertigungs- und Absatzaktivitäten. Der Wettbewerb steigt und so wird es auch für immer mehr kleine und mittelständische Unternehmen (KMU) zur Notwendigkeit, die Möglichkeiten einer globalen Beschaffung auszuschöpfen, um marktgerechte Produktpreise zu erzielen sowie Marktanteile im In- und Ausland zu sichern. Im Folgenden wird eine Methode vorgestellt, welche den strategischen Einkäufern von KMU als Leitfaden in einem fachbereichsübergreifenden Strategieentwicklungsprozess dient. Dabei sind insbesondere die Wirkzusammenhänge zwischen Bauteil, Beschaffungsmarkt und der eigenen Unternehmensorganisation zu analysieren.

Erfolgreiche deutsche Produktionsunternehmen haben sich in Zusammenhang mit der Konzentration auf ihre Kernkompetenzen und der Nutzung internationaler Standortvorteile in Form globaler Wertschöpfungsnetzwerke aufgestellt. Die fortschreitende globale Einbindung von unternehmensinternen Werken sowie externen Partnern und Zulieferern begünstigt jedoch komplexe Wirkungsmechanismen innerhalb der Netzwerke, die teilweise oder vollständig unbekannt und schwer prognostizierbar sind. Möchten deutsche Produktionsunternehmen auch zukünftig die positiven Effekte der Globalisierung nutzen, müssen sie in der Lage sein, die sich dramatisch ändernden Einflussfaktoren globaler Wertschöpfungsnetzwerke zu beherrschen. Diesbezüglich gewinnen wandlungsfähige Wertschöpfungsketten, die sich flexibel und reaktionsschnell an die dynamischen Herausforderungen anpassen, an Bedeutung. Der vorliegende Artikel beschreibt einen Ansatz zur Planung und Optimierung wandlungsfähiger globaler Wertschöpfungsnetzwerke. Grundlage ist das Vorgehen des im September 2010 gestarteten Verbundforschungsprojektes „Planung und Optimierung von wandlungsfähigen globalen Wertschöpfungsnetzwerken“ (POWer.net)

Zunehmender weltweiter Wettbewerb, volatile Nachfrage bei gestiegenen Kundenansprüchen, zunehmende Prognoseunsicherheiten, Verschiebungen im Produkt- und Variantenportfolio während des Lebenszyklus bei gleichzeitig abnehmender Dauer der Lebenszyklen sowie steigendem Kostendruck stellen die Automobilindustrie heute vor herausfordernde Aufgaben. Die Optimierung von Entwicklungsprozessen, welche die Basis für den späteren Erfolg eines Produktes am Markt festlegen, ist Teil des Geschäftsprozessmanagements, um schlussendlich die zukünftige Wettbewerbsfähigkeit des Unternehmens zu sichern.

Bei Strukturen mit Toleranzen im Submikrometerbereich erlauben es selbst modernste Messsysteme nicht, Fertigungs- und Messprozess zu separieren. Überwachung und Regelung der Fertigungsstreuung basieren auf überlagerten Daten und bleiben daher meist erfolglos. Am Karlsruher Institut für Technologie (KIT) gelang mit einem neuartigen Qualitätsregelkarten-Design die Trennung von Fertigungs- und Messstreuung.

Am wbk Institut für Produktionstechnik wurde eine Handhabungs- und Bearbeitungskinematik entwickelt, die sich aus einer seriellen Kinematik und einer Parallelkinematik zusammensetzt. Das Institut für spanende Fertigung ISF in Dortmund befasst sich u.a. mit der mechanischen Bearbeitung von dünnwandigen Leichtbaustrukturen. Gemeinsame Untersuchungen zum Fräsen von Aluminiumstrangpressprofilen am neuen Maschinenkonzept und an einem konventionellen dreiachsigen Bearbeitungszentrum zeigen die aktuellen und künftig erreichbaren Möglichkeiten und Präzisionsgrenzen der Kinematik auf.

Gerade in konjunkturschwachen Zeiten versuchen Unternehmen aller Größenordnungen durch innovative Dienstleistungen die Bindung ihrer Kunden zu erhöhen, um rückläufige Umsätze mit Neumaschinen aufzufangen. Allerdings stoßen nicht alle von den Anbietern als innovativ formulierten Dienstleistungen auf die Akzeptanz der Kunden. Im Rahmen des Forschungsprojekts „Wissenstransfer und Grundlagenbereitung für technische Dienstleistungen im Maschinenund Anlagenbau (WiTal)“ wurde eine umfassende Potenzialanalyse in Form einer Unternehmensbefragung durchgeführt, um zu untersuchen, welche Dienstleistungen für Kunden und Anbieter zukünftig von besonderer wirtschaftlicher Relevanz sind. Der Fokus liegt dabei auf so genannten verfügbarkeitswirksamen technischen Dienstleistungen, die zum einen das Ausfallverhalten von Produktionssystemen berücksichtigen und zum anderen die Verfügbarkeit des Produktionssystems direkt verbessern. Im Folgenden werden die Herangehensweise bei der Potenzialanalyse sowie die detaillierten Ergebnisse der Analyse vorgestellt.

Die Umwelt der Produktion, insbesondere die Beschaffungs- und Absatzmärkte, gestalten sich zunehmend dynamisch, Produktlebenszyklen werden kürzer und Kunden sind bezüglich der Individualisierung der Produkte anspruchsvoller geworden. Die Komplexität der Produktionssysteme selbst wird durch eine zunehmende räumliche Verteilung einzelner Prozesse auf mehrere Standorte sowie durch den globalen Kostendruck erhöht. Die frühzeitige Berücksichtigung von Lebenszykluskosten in der Planung zukünftiger Produktionssysteme erfordert folglich den adäquaten Umgang mit Unsicherheiten. Am Institut für Produktionstechnik (wbk) des Karlsruher Instituts für Technologie (KIT) wird derzeit eine Methodik zur Bewertung und Optimierung von Produktionssystemen entwickelt, die ein Produktionssystem beginnend in frühen Planungsphasen bis zum Ende des Lebenszyklus begleitet. Im Folgenden wird das Grundmodell zur Bewertung unter Berücksichtigung relevanter Unsicherheiten vorgestellt, das Grundlage für eine spätere, angestrebte dynamische Optimierung ist.

Durch dir Erhöhung der Variantenvielfalt verstärken sich die Herausforderungen in allen Bereichen eines Unternehmens. Kern ist die Fragestellung nach der optimalen Flexibilität der eingesetzten Produktionssystem. Vor allem in der Angebotsphase eines neuen Produkts liegen meistens noch sehr wenig Daten über zukünftige Stückzahlverläufe und Variantenoptionen vor. Dies erschwert eine genaue Analyse des Kostenverhaltens bei der Herstellung und damit eine optimale Auswahl und Gestaltung des Produktionssystems.

Um einerseits die durch technologischen Fortschritt wachsende Energienachfrage zu decken und andererseits die CO2- Emissionen zu reduzieren, die durch die Verbrennung von fossilen Brennstoffen entstehen, werden in den letzten Jahren diverse Energiequellen erschlossen. Anforderungen dabei sind, dass die Energiequelle für menschliche Maßstäbe kontinuierlich zur Verfügung steht, durch die Energiewandlung im besten Fall kein CO2 entsteht und keinerlei Risiken für den Menschen ausgehen. Alle drei Kriterien werden durch die Wandlung von kinetischer Windenergie in elektrische Energie durch Windkraftanlagen (WKA) erfüllt. Die Herausforderung innerhalb der Windkrafttechnologie ist, die Herstellungskosten pro Kilowattstunde zu senken, um mit klassichen Technologie der Energieerzeugung wettbewerbsfähig zu sein. Zielsetzung des vom wbk entwickelten Ansatzes ist die Senkung der Kosten pro Kilowattstunde Windkraft durch die Minimierung der Instandhaltungskosten mit Hilfe eines lastabhängigen Zuverlässigkeitsmodells und der statistischen Optimierung der Instandhaltungskapazitäten.

Die zunehmende Erhöhung der Variantenvielfalt von Produkten stellt eine Herausforderung an alle Bereiche der Unternehmung dar. Im Kontext der Produktion heißt dies vor allem eine optimale Flexibilität der eingesetzten Produktionssysteme zu finden. Zu dem Zeitpunkt strategischer Marktentscheidungen liegen meistens noch sehr wenige Daten über Stückzahlverläufe und Variantenoptionen eines Produktes vor, sodass eine Analyse der Herstellkosten und damit eine optimale Auswahl und Gestaltung des Produktionssystems schwierig ist. Im Rahmen des Verbundforschungsprojekts VireS (Virtuelle Synchronisation von Produktentwicklung und Produktionssystementwicklung) wurde am Institut für Produktionstechnik (wbk) der Universität Karlsruhe ein Simulationsalgorithmus entwickelt und implementiert, der ausgehend von den in frühen Planungsphasen verfügbaren Daten den Kostenverlauf eines Produktionssystems in Abhängigkeit von Varianten- und Stückzahlbereichen über dessen Lebenszyklus abbildet. Dabei spielen stochastische Umwelteinflüsse eine zentrale Rolle.

Aufgabenstellung des Forschungsprojekts HyPlan ist die Konzeption eines softwaregestützten Planungswerkzeugs, mit dem Fertigungsplaner in kleinen und mittelständischen Unternehmen bei Neu- oder Umplanungen von Produktionssystemen sowie deren Anpassung an sich ändernde Rahmenbedingungen unterstützt werden. Im Projekt werden zwei Fragestellungen vertieft. Zunächst, wie kann das Zusammenwirken von Mensch und Computer im Planungsprozess optimal gestaltet werden (hybride Planung)? Des Weiteren, wie kann das Produktionssystem über seine gesamte Lebensdauer hinweg systematisch an Veränderungen der betrieblichen Rahmenbedingungen angepasst werden (Adaption)? Dieser Artikel fokussiert auf das Zusammenwirken von Mensch und Computer im Planungsprozess. Dazu vertieft er die grundlegenden Konzepte des hybriden Planungswerkzeugs.

Durch immer kürzer werdende Produktlebenszyklen gewinnt das Thema der Innovationsgeschwindigkeit zunehmend an Bedeutung. Verluste durch einen verspäteten Markteintritt können im Produktlebenszyklus nicht mehr kompensiert werden. Speziell bei Produkten, die nicht von einem Hersteller alleine, sondern auf grund Grund ihrer Komplexität oder ihrer technischen Besonderheiten im Verbund mit anderen Unternehmen entwickelt und hergestellt werden, gestaltet sich der Innovationsprozess zunehmend langwierig und zeitaufwändig. Im vorliegenden Artikel wird eine im Forschungsprojekt „Innovationen in verteilten Engineering-Netzwerken (Engineering.net)“* entwickelte Konfigurationsmethodik für verteilte Entwicklungsnetzwerke vorgestellt, die den Anwender unterstützt, geeignete Partner für das Entwicklungsvorhaben zu identifizieren und das Entwicklungsnetzwerk bereits im Vorfeld zu bewerten. Integriert wird diese Vorgehensweise in ein Konstrukt aus mehreren Methoden, deren Kombination ein umfassendes Vorgehensmodell zur Gestaltung von Prozessabläufen in verteilten Entwicklungsnetzwerken ergibt.

Im Rahmen des Sonderforschungsbereich Transregio 10 (SFB/TR 10) “Integration von Umformen, Trennen und Fügen für die flexible Fertigung von leichten Tragwerkstrukturen” wird eine Prozesskette zur produktflexiblen Kleinserienfertigung von Space-Frame-Rahmenstrukturen aufgebaut. An diesem Forschungsprojekt sind Institute der Technischen Universität Dortmund, der Technischen Universität München und der Universität Karlsruhe (TH) beteiligt. Um bereits frühzeitig die Qualität und die Zuverlässigkeit der Prozesskette zu verbessern, wurde in einem standortübergreifenden Qualitätsarbeitskreis eine System-FMEA Prozess für die einzelnen Teilprozesse durchgeführt. Mit dieser konnten projektbegleitend potenzielle Fehlerschwerpunkte ermittelt und gezielt Gegenmaßnahmen eingeleitet werden. Im folgenden Artikel werden die eingeleiteten Fehlervermeidungsmaßnahmen für die am SFB/TR 10 beteiligten Prozesse und Verfahren beschrieben. Die Prozesse sind im Einzelnen: Das mehrachsige Runden beim Strangpressen sowie das darauf folgende fliegende Abtrennen zur Herstellung der Rahmenelemente, eine flexible und intelligente Greiftechnik in Kombination mit einer Handhabungs- und Bearbeitungskinematik zur spanenden Bearbeitung sowie als letzte Schritte die Verfahren Innenhochdruckfügen, Rührreibschweißen und Laserstrahlschweißen zum Fügen der Einzelteile zu einer Rahmenstruktur.

Im Maschinen und Anlagenbau wird zunehmend nicht nur der Beschaffungspreis als entscheidendes Kaufargument, sondern auch die gesamten Kosten einer produktionstechnischen Maschine oder Anlage über ihren gesamten Lebenszyklus genannt. In diesem Rahmen sind technische Dienstleistungen in der Lage, die Lebenszykluskosten einer Maschine zu reduzieren. Eine Möglichkeit zur Prognose von Ausfallkosten und damit zur Quantifizierung des Nutzens technischer Dienstleistungen stellt der vom wbk entwickelte Servicekonfigurator dar. Hersteller und Betreiber von Anlagen und Maschinen erhalten mit dem Servicekonfigurator die Möglichkeit, die durch das Ausfallverhalten verursachten Kosten zu ermitteln und sie dem Nutzen aus einer Verfügbarkeitssteigerungen durch die Inanspruchnahme von technische Dienstleistungen gegenüberzustellen.

Ausgehend von der Automobilindustrie führen zunehmend Unternehmen anderer Branchen ihr eigenes Ganzheitliches Produktionssystem (GPS) ein. Das Institut für Produktionstechnik (wbk) nahm diesen Trend zum Anlass, das Thema mit hochrangigen Führungskräften ausgewählter Industriepartner zu diskutieren. Der folgende Artikel gibt einen kurzen Einblick über die Erkenntnisse der Kurzstudie bezüglich der wesentlichen Merkmale Ganzheitlicher Produktionssysteme wie Motivation, Ausprägung, Einführungsstrategie, sowie Aufwand und Nutzen. Abschließend wird der Handlungsbedarf zur Weiterentwicklung von GPS erörtert.

In der Verkehrstechnik nimmt die Bedeutung leichter, selbst tragender Rahmenstrukturen, so genannter Space-Frame-Rahmen, kontinuierlich zu. Die Rahmenbauweise bietet ein hohes Leichtbaupotenzial, bringt jedoch auch hohe fertigungstechnische Herausforderungen mit sich. Ein im Sonderforschungsbereich* Transregio 10 erarbeiteter neuartiger Maschinenprototyp ermöglicht die produktflexible Bearbeitung dreidimensional gerundeter Rohrprofile mit geringem technischen Aufwand. Um eine gute Bearbeitungsqualität zu gewährleisten, ist die präzise Positionierung des Werkstücks erforderlich. In ersten Versuchen zur Positionierungsgenauigkeit konnte gezeigt werden, dass die absolute Genauigkeit jedoch noch nicht dem angestrebten Ziel entspricht. Aus diesem Grund wurde ein Ansatz zur Feinpositionierung erarbeitet, bei dem Sensorwerte an die Steuerung übergeben werden und anschließend die Ausgleichsbewegung berechnet und durchgeführt wird. Durch die Feinpositionierung kann die Genauigkeit deutlich erhöht werden.

Der stetig wachsende Bedarf an leichten Tragwerksstrukturen, wie sie häufig in der Verkehrstechnik zur Anwendung kommen, fordert neuartige Prozessketten zur kostengünstigen, automatisierten und produktflexiblen Kleinserienfertigung von Space-Frame-Rahmenstrukturen. Im Rahmen des Sonderforschungsbereichs Transregio 10 (SFB/TR 10) mit dem Titel „Integration von Umformen, Trennen und Fügen für die flexible Fertigung von leichten Tragwerkstrukturen“ entstand in der ersten Bewilligungsphase seit November 2002 eine Prozesskette mit neuartigen Maschinen- und Handhabungskonzepten zur Herstellung und Bearbeitung räumlich gekrümmter Strangpressprofile. Der folgende Artikel stellt die prototypisch realisierte Maschinentechnik vor und gibt einen Ausblick auf eine in die Prozesskette zu integrierende Qualitätssicherung.

Ein Produktionsanlauf ist gekennzeichnet durch das komplexe Zusammenwirken von Geschäftsprozessen, die die Ausbringung des Produktionssystems bestimmen. Im vom BMBF geförderten Projekt* "ProactAS - Proaktive Anlaufsteuerung entlang der Wertschöpfungskette" wird untersucht, inwieweit sich wesentliche Anlaufergebnisgrößen wie Produktionsmenge, -kapazität und -qualität im Verlauf eines Anlaufes verändern. Auf Grund der hohen Komplexität wird hierzu ein Prognosesystem bestehend aus einer Wirkbeziehungssystematik und einer Simulation entwickelt. Die Simulation setzt sich aus zwei Teilsystemen zusammen: einer Materialflusssimulation und einer Qualitätssimulation. Auf diese Weise kann eine ganzheitliche Anlaufsimulation erzeugt werden, indem qualitätsrelevante Aspekte wie die Fähigkeitsentwicklung von Geschäftsprozessen in die Materlaiflusssimulation integriert werden. Der Artikel stellt die Funktionsweise beider Simulationsinstrumente vor und beschreibt, wie eine Verknüpfung gelingt. Das Zusammenspiel wird anhand eines Simulationsszenarios gezeigt und mit einer prototypischen Implementierung getestet. Der Artikel endet mit einem Ausblick auf weitere Potenziale und Möglichkelten der beschriebenen Simulationstechniken.

Kundenindividuellere Produkte, steigender Wettbewerbs- und Kostendruck in Verbindung mit sich stetig verkürzenden Produktlebenszyklen erhöhen die Bedeutung des Produktionsanlaufs innerhalb einer Organisation [1]. Die Fähigkeit, Produkte schneller als die Konkurrenz zu entwickeln, zu produzieren und am Markt zu positionieren, entscheidet zukünftig verstärkt über finanziellen Erfolg oder Misserfolg eines Unternehmens [2]. Hierbei gewinnt die Beherrschung der Produktionsanlaufprozesse an Bedeutung. Eine Verbesserung von am Produktionsanlauf beteiligten Prozessen bedeutet eine Qualitätssteigerung und damit zeitliche Verkürzung von Produktionsanläufen. Die am Institut für Produktionstechnik (wbk) der Universität Karlsruhe (TH) und im BMBF-geförderten Projekt ProactAS [3] entwickelte prozessbasierte Qualitätsprognose unterstützt den Anlaufmanager bei der Kontrolle und Prognose seiner Geschäftsprozesse im Produktionsanlauf. Die Qualitätsprognose bietet so eine Möglichkeit, prozessbasierte Störungen frühzeitig zu erkennen und effiziente Maßnahmen zur Störungsbeseitigung einleiten zu können.

Explainable artificial intelligence (xAI) has become a popular subject of research amongst AI scholars in the last years. Some scholars consider xAI a significant driver of AI adoption in practice. However, at date, only a few studies investigated the conditions under which xAI solutions provide benefits in practice. Additionally, there is still a lot of controversy and inconsistency about related terminology revealing large conceptual differences between the understanding of explanations from a theoretical social science viewpoint and from a technological viewpoint. In this article, we strive to contribute to a more realistic picture of the potential and practical application scenarios of xAI. Thereby, we clarify the question whether xAI is a key driver for AI adoption, a mistaken concept from a theoretical point of view or perhaps a practically irrelevant feature and bridge the gap between different disciplines.

The strategic configuration of global production networks is shaped by a variety of influencing factors and strategic motives. In addition to cost factors, intangible factors such as employee qualification and supplier reliability in particular influence the network configuration. This paper examines the relevance of 30 influencing factors on network configuration as well as their consideration in decision-making. The study shows that intangible factors are often only included through managers’ gut feelings, although they have a significant influence on network performance. However, it can be shown that with increasing perceived relevance, intangible factors are included more systematically in the decision-making process.

Nowadays battery cells are produced in high volumes and with no customization for lower demand quantities. Since battery technology is still evolving rapidly and production systems are an expensive, long-term investment, there is a need for adaptability of the production system to changing markets and technologies. This paper presents an approach to evaluate different configurations of a highly flexible production system for battery cells in different scenarios with the help of a digital twin and the definition of optimal system configurations. This permits the definition of a change strategy on how to move from one configuration to another.

Customer specific, individual products nowadays lead to larger product variance and shorter time to market. This requires efficient production system planning. In addition, due to a larger system complexity, each iteration of the planning process itself gets soaringly complex. Time constraints and complexity, therefore, emphasize the necessity of supporting humans in planning modern production systems. Especially the determination of the production sequence holds immense potential and tends to get even more complex within specific production technologies. Exemplarily, this article focuses on welding sequences. Here, domain knowledge from product development and production planning needs to be holistically integrated. Furthermore, implicit, historic knowledge needs to be formalized and used in today’s planning tasks. This article introduces a methodical approach and a corresponding toolchain to derive optimal production sequences from customer product data which is validated using welding processes. For this, firstly, a reference system is build up consisting of historic product data (e.g. part list, CAD data) and corresponding production system characteristics (e.g. number and specifications of machines). The main aspect is to use similarities between the new product variant and assemblies from the reference system, to determine implications of product specifications on the process sequence. Overall, such restrictions can be displayed using Model-Based Systems Engineering. Relevant information (e.g. weld seam lengths) can be used to compute the optimal weld seam order regarding minimal cycle times, for example. This requires a parametric encoding of product and production system. In a nutshell, this approach covers the automated derivation of an optimal production sequence for new product variants, based on system information and product similarities, to tackle time constraints and complexity by suggesting initial planning drafts.

Smart Product-Service Systems (sPSS) offer the opportunity to create additional value by combining smart products with smart services. However, industry players often lack resources, know-how, and practical guidance to develop, introduce, and maintain such complex solutions. To support their innovation efforts, research first needs to understand the implications of applying these emerging technologies. Hence, we present a maturity model for sPSS to describe and compare such solutions using twelve dimensions and conduct a case study to illustrate the model. Our research combines insights from a systematic literature review, 20 real-world use cases, seven interviews with sPSS experts, and a focus group.

There are plenty of human-centred research questions in production science. So far, the focus of the analysis is skewed towards technical considerations. Decision experiments, however, provide a promising approach to gain insights from a human perspective by using learning factories as field-in-the lab environments. This article reports operative insights and qualitative results from a decision experiment in the learning factory. Participants assemble electronic servo motor components and are paid according to their productivity. The adjustment to the learning factory as a lab environment and modifications to production stations in the learning factory that allow for a rigorous data collection are described. Furthermore, as a proof of concept, this article states how the setup was perceived by four participants that were sampled and interviewed in a technical pilot. Overall, participants stated a high level of satisfaction and engagement with the task and were not distracted by noise. Since other activities naturally take place in learning factories during experimental sessions, participants were asked about whether they felt observed by bystanders, which was confirmed to some extent. This article discusses remedies to these effects for future experiments. Finally, a list of essential questionnaire items that should be contained in decision experiments in learning factories in general is presented. Using these insights, decision experiments in learning factories can push the envelope in human-centred production science.

Digitalization and Industry 4.0 have a major impact on work processes, human interaction and leadership in many workplaces, one of them being production. For employees, this results in a change of work tasks and job requirements. Therefore, digitalization and Industry 4.0 create a need for extensive competence development of the workforce. Especially, SFM currently undergoes an immense transformation. Due to an increasing availability and quality of real-time data, new forms of collaboration in production become possible. These possibilities can lead to an improvement regarding production processes, hence, developing or maintaining a competitive advantage. One example is the concept of autonomous assembly teams, which have a high degree of autonomy in their work planning, work prioritization, continuous improvement and problem solving activities. This article presents a holistic approach for a definition and analysis of relevant competences for employees in the production sector. Based on this analysis, a modular training concept is designed to improve the identified competences in learning factories. This is followed by an explanation, which enables employers and employees to identify their need for competence development and how to select specific training modules. Finally, we present a universal approach to implement these modules in different learning factories.

An increasing awareness of sustainability and scarcity of resources requires to enhance a product’s lifetime. Within the context of a circular economy, remanufacturing therefore can be applied. Used products (so-called ‘cores’) are returned to at least their original performance. An efficient planning and management of reverse supply chains (RSC) is a prerequisite for successful remanufacturing. Besides the required material flow from the customer via service centers, collection stations, and core brokers to the remanufacturing plants, the reverse flow of core information is essential. The multi-tier exchange of core information potentially facilitates reducing existent uncertainties in RSC, i.e. regarding timing, quantity, and quality of returned products. Yet, current approaches neither consider the multi-tier information flow nor the differentiation of core information for different downstream tasks in detail. Specifically, information flow in the automotive RSC remains to be researched in detail. Therefore, the potential of an increased exchange of core information for remanufacturing in RSC is explored in this paper. A literature review and expert interviews with the stakeholders in the automotive RSC are conducted to assess the status quo of information exchange. Based on this, relevant core-specific information, and their impact on increasing the efficiency of different downstream planning processes are identified. To quantify the potential of an increased information exchange, both a model for the categorical use of information and a receptor model are developed. It can be concluded that an increase in the exchange of information in remanufacturing goes along with a multitude of facilitations, e.g. regarding logistics optimization, material requirement planning and stochastic routing of cores. Moreover, due to the prioritization of core information, a sequence model for core information retrieval can be derived.

Computed tomography (CT) is a flexible measurement method for a variety of metrological tasks. However, to achieve reliable and accurate measurements, interrelated setting parameters must be chosen. The workpiece orientation is one of such parameters, especially for multimaterials. Current approaches to support optimal orientation do not adequately consider the effect on accuracy in complex measurement tasks. Additionally, only few experimental studies provide the therefore necessary insights. Consequently, this study aimed to investigate the influence of orientation of a multimaterial workpiece on the subsequent evaluation and measurement process. For this purpose, a workpiece containing multiple features was scanned in a total of 14 orientation configurations and the resulting effects on both image (based on contrast-to-noise-ratio) and measurement quality (based on measurement accuracy) were investigated. It was shown that components measurable in the medium power range of a CT system have a wide range of optimal angles for optimal orientation. The image quality is suited for its identification.

Customer specific, individual products nowadays lead to larger product variance and shorter time to market. This requires efficient production system planning. In addition, due to a larger system complexity, each iteration of the planning process itself gets soaringly complex. Time constraints and complexity, therefore, emphasize the necessity of supporting humans in planning modern production systems. Especially the determination of the production sequence holds immense potential and tends to get even more complex within specific production technologies. Exemplarily, this article focuses on welding sequences. Here, domain knowledge from product development and production planning needs to be holistically integrated. Furthermore, implicit, historic knowledge needs to be formalized and used in today’s planning tasks. This article introduces a methodical approach and a corresponding toolchain to derive optimal production sequences from customer product data which is validated using welding processes. For this, firstly, a reference system is build up consisting of historic product data (e.g. part list, CAD data) and corresponding production system characteristics (e.g. number and specifications of machines). The main aspect is to use similarities between the new product variant and assemblies from the reference system, to determine implications of product specifications on the process sequence. Overall, such restrictions can be displayed using Model-Based Systems Engineering. Relevant information (e.g. weld seam lengths) can be used to compute the optimal weld seam order regarding minimal cycle times, for example. This requires a parametric encoding of product and production system. In a nutshell, this approach covers the automated derivation of an optimal production sequence for new product variants, based on system information and product similarities, to tackle time constraints and complexity by suggesting initial planning drafts.

Customer satisfaction is a key factor to ensure long-term business success. Therefore, automotive manufacturers offer various options to individualize a car. Furthermore, customers and dealers are allowed to change their configuration until the vehicles are scheduled for production. This point is called order freeze. While vehicle specifications remain nearly unchanged in a build-to-order fulfillment strategy, this is not the case in build-to-stock. Mass-customized products with billions of possible car configurations, changing customer demands, or a dynamic environment are some of the challenges that confront the manufacturers in the planning and ordering processes. In this paper, the concept of multiple option-specific order freeze points is developed, which allows customers and dealers to change the configuration specifications at an even later point. For this purpose, the planning process, customer preferences, feasibility rules as well as technical and sales-operated option dependencies are evaluated. Furthermore, independent option-specific order freeze points are detected based on data-driven methods to handle the requirements for agile production systems by using current analytical technologies. The concept of multiple option-specific order freeze points has a high potential to be applied in a practical usage and is validated by a real-world use case of the Dr. Ing. h.c. F. Porsche AG.

Recently, traceability systems have become more common, but their prevalence and design vary significantly depending on the industry. Different law and customer-based requirements for traceability systems have led to diverse standards. This contribution offers a framework to compare the state of traceability systems in different industries. A comparison of industry characteristics, motivations for traceability system implementation, common data management, and identification systems are offered. Upon that analysis, the potential of cross-industry traceability systems and approaches is identified. This extended usage of traceability systems supports the quality assurance, process management and counterfeit protection and thus expands customer value.

Increasingly shortening product life cycles, regional market challenges and unforeseeable global events require highly iterative product and production adaptions. For faster adaptation, it is necessary to have a systematic understanding of the relationships between product design and production planning. A unified model and data structure are fundamental. Basic data must be extracted from both domains and integrated for consistent product-production co-design. For this purpose, we use a biological analogy, the genome-proteome phenomenon, to model the interdependencies of product (customer needs, functional requirements, design parameters) and production (technologies capabilities, machine information, process chain alternatives). From the genome, which represents the totality of available data of product and production, we contextualize the proteome, which represents an instance of a concrete product design and the corresponding production configuration. Thereby, one gene represents one incremental information set consisting of all above mentioned product and production information for a specific product function. For each of the mentioned information domains (e.g. product requirements) within a gene, a methodology exists (e.g. NLP) to model the interlinkage to the adjacent information domain (e.g. product function). Utilizing the interdependencies and heredity of product design and production planning enables quick analysis of adaptation-induced impact which will provide enhanced competitiveness in a volatile world.

Since current battery cell production lines are not flexible regarding format and material, it is necessary to develop new production systems. It is also required to develop this production line as an agile system in order to be able to flexibly counteract unit-specific capacity fluctuations. In addition, only low scrap rates are allowed when integrating new material systems which requires a holistic in-process or in-line control and the associated quality assurance. Agile produc-tion systems open up new possibilities for developing the battery cell product. Therefore, this article will present a novel product-production co-design that can be specifically adapted to customer requirements.

In times of globalization and digitalization, silo mentality and protectionism lead to competitive disadvantages for all partners of a production network. High scrap rates and low supplier margins in the production of high-precision products can be identified as resulting inefficiencies. Supply chain collaboration can contribute to significantly increase product quality by simultaneously reducing the associated costs, globally. We introduce batch allocation as a data-driven method for cross-company quality control of differing component batches based on both, supplier data and internal data. The industrial application is demonstrated within a global production network for manufacturing high-precision products.

The dynamic and highly complex task of production network management requires decision support through quantitative models. In the industrial praxis, these models are specifically designed and implemented for particular management decisions, requiring significant one-time effort for model creation. This contribution utilizes the digital twin concept to facilitate production network models that are continuously synchronized with the examined production network to support several different management decisions. The approach structures data from existing information systems as a synchronized generic base model, which is used to create problem-specific executable models, thereby saving costs through repeated model use and quicker decision making.

Existing implementation strategies for Industry 4.0 and Digital Shopfloor Management often focus on technology. This is accompanied by a lack of transparency regarding production processes and information structures, often preventing decentralised decision-making by employees. Thus, the implementation of I4.0 requires a socio-technical implementation approach that takes human, technology and organization into account. This work presents a model to implement Industry 4.0 combining the dimensions of people, technology and organization. The approach supports companies in adapting their socio-technical work system to include digitalisation. Taking the example of Digital Shopfloor Management, a socio-technical implementation strategy is developed and associated acceptance methods are derived. This pro-cedure ensures that the potential of Industry 4.0 can be achieved and …

Due to the variety and interaction of volatile influencing factors as well as the increasing requirements resulting from individualization, the prediction of future demand development is becoming increasingly difficult and complex. In manufacturing companies, this leads to a need for shorter and faster production planning cycles. In addition, the production network must be secured against uncertainty. This is possible by scenario analysis integrated into automated planning. In this paper, an automated scenario analysis in combination with deterministic modeling for integrated product allocation and global network configuration is developed to tackle demand uncertainty in a medium-term planning horizon. When creating scenarios, a trade-off arises concerning the completeness of possible developments and the manageability of the set. The objective is to achieve a representative coverage of possible future states by a small number of reasonable scenarios. Therefore, change drivers are defined that can lead to modifications of customer orders. This is followed by an automated simulation of the occurrence of the change drivers using a Monte Carlo simulation with a high number of samples for statistical validation. A cluster analysis with upstream principal component analysis is used to reduce the number of scenarios while maintaining representativeness. Finally, the scenarios are optimized in a production planning tool. The approach is applied to a real use case. The results are used to validate the representativeness of the scenarios, as well as to conclude robust decisions.

Digital twins of production systems enable new forms of production control, flexibility and continuous improvement. While off-the-shelf software for discrete-event simulation permits the fast implementation of rough simulation models with sufficient accuracy for project-based analysis, they lack the precision and generality of a digital twin. This paper presents an approach to close the gap between model and reality by continuous and iterative updates enabled by connecting the simulation model to IT systems and smart data analysis. However, handling different databases requires a generative and flexible modelling approach as well as suitable algorithms for probability distribution estimation and control logic identification. The presented approach was validated at a real world example from the automotive industry where an average deviation of output to reality per week of 0.1% was achieved, proving the effectiveness of the approach.

In an environment which is marked by an increasing speed of changes, industrial companies have to be able to quickly adapt to new market demands and innovative technologies. This leads to a need for continuous adaption of existing production systems and the optimization of their production control. To tackle this problem digitalization of production systems has become essential for new and existing systems. Digital twins based on simulations of real production systems allow the simplification of analysis processes and, thus, a better understanding of the systems, which leads to broad optimization possibilities. In parallel, machine learning methods can be integrated to process the numerical data and discover new production control strategies. In this work, these two methods are combined to derive a production control logic in a semi-automated production system based on the chaku-chaku principle. A reinforcement learning method is integrated into the digital twin to autonomously learn a superior production control logic for the distribution of tasks between the different workers on a production line. By analyzing the influence of different reward shaping and hyper-parameter optimization on the quality and stability of the results obtained, the use of a well-configured policy-based algorithm enables an efficient management of the workers and the deduction of an optimal production control logic for the production system. The algorithm manages to define a control logic that leads to an increase in productivity while having a stable task assignment so that a transfer to daily business is possible. The approach is validated in the digital twin of a real assembly line of an automotive supplier. The results obtained suggest a new approach to optimizing production control in production lines. Production control shall be centered directly on the workers' routines and controlled by artificial intelligence infused with a global overview of the entire production system.

Despite continuous improvements in modelling, software tools and data availability, simulation projects of production systems still require a lot of manual effort, expertise in various disciplines and time. In many projects the high initial invest for building the simulation model is followed by a rather short period of experimentation and analysis. As production systems have to be adapted at an increasing pace to respond to rapidly changing markets and business environments, simulation models of these systems become outdated earlier, reducing their useful time window. One way to extend this time window would be the implementation of a method of automated comparison with the current production systems and subsequent self-adaption of the model to reality to maintain and even improve its accuracy over time. This approach will be presented and validated at a real world use case. Such an enhanced simulation model can be called a digital twin of the production system.

High strength steels are important in terms of lightweight, safety and economical aspects for mobility concepts of the future. In fact, machined surfaces and its characteristics are essential for the entire product-lifecycle. In the presented work, the capability of micromagnetic nondestructive-testing (NDT) techniques combined in 3MA, and optimal working point determination to detect critical surface states such as white layer (WL) associated to hardness increase and its characteristics is discussed. An outlook is given how in terms of Industry 4.0 production-integrated determination of material characteristics can enable in-line monitoring and closed-loop control for an optimization of production processes.

Remanufacturing, previously characterised by manual and cost-intensive processes, is a decisive step towards a resource-conserving circular economy. Uncertain product states, inconsistent quality, and fluctuating availability of end-of-life products not only pose major challenges for the automation of remanufacturing, but also for intralogistics, which has hardly been considered in the literature to date. This paper gives a concept overview on an ontology-based autonomous intralogistics system embedded in the fluid automation framework, describes and illustrates the main cyber-physical components and shows exemplary workflows. The presented concept is currently implemented as part of the AgiProbot research project.

Today, data-sharing along global supply chains and outsourcing to international vendors are ubiquitous trends in global production. Both trends are a form of so-called interfirm collaboration. Previously, research focused on specified tools to gain advantages from interfirm collaboration. However, possible risks and structural obstacles hamper partners to engage in collaborative relationships. In this paper, a framework is presented to monitor the maturity of a firm?s interfirm relationships. Thus, key factors and distinct dimensions are proposed that determine success in interfirm collaboration. The concluding framework visualizes interfirm relationships and creates transparency between collaborating stakeholders.

A central challenge in the implementation of digitalisation and Industry 4.0 in companies is the human-centred development and design of the new technologies. These technologies have a major impact on the way people work and thus also on the motivation and satisfaction of employees. A thorough understanding of underlying drivers of employees' technology acceptance and possible resistance to change is crucial for a successful implementation of such technologies. Experimental economic research methods comprise a way to record the effects on human behaviour and working methods allowing for causal evidence. Controlled laboratory conditions offer the option to vary only individual variables and measure their influence on human behaviour, motivation, satisfaction, or working methods. In contrast to standard computer labs, learning factories offer the possibility to carry out experiments in a real production environment and thus observing behaviour in real work tasks in a realistic environment. This leads to increased external validity while at the same time the strict experimental protocol still allows making causal claims. Learning factories so far do not fulfil laboratory requirements. We first outline the prerequisites for the execution of empirical experiments. We then introduce our research concept, based on the example of the Learning Factory Global Production of wbk. The goal of this paper is to create an environment that allows collecting empirical and meaningful research data in a learning factory. Finally, we exemplify our concept with an experimental design on how digitalisation can foster decentralised decision-making. This research will inform a more human-centred design of digitalisation technologies and its effects on employee behaviour.

Engineering competence and the digitization of all processes along the product development process are highly decisive for today's success of industrial companies. The design process is very individual and strongly based on design engineers' experience. Part of this knowledge and the result of the design approach are fixated in the existing variations of the product generations, but are difficult to extract and to formalize. Conclusions about design-related patterns between products of different generations or variants can be drawn from the model tree representing the design engineer?s thinking process for each individual CAD model. However, the model tree has hardly been used so far. The aim of this paper is to examine whether there exist any common design patterns between CAD models of certain component classes by the exemplary use case in the area of mechanical engineering. To identify patterns and to extract knowledge out of complex data sets, Machine Learning (ML), especially Deep Learning, has proven an immense capability. Finally, based on the learned patterns, meaningful next design steps are to be proposed in the form of an assistance system. The results show that there exist common design patterns for various classes of components. It is illustrated on an exemplary component class that those patterns can be used to train an assistance system based on Recurrent Neural Networks (RNNs). The corresponding design patterns were extracted from data of an industrial application partner. By transferring these design patterns to the development of new product generations or variants, on the one hand the design process itself and thus the time to market can be shortened. On the other hand, the knowledge from previous product generations contained in those patterns can be preserved. For further research the design patterns of CAD models extracted by ML algorithms is a contribution to faster knowledge extrapolation.

Production systems must be able to quickly adapt to changing requirements. Especially in the field of remanufacturing, the uncertainty in the state of the incoming products is very high. Several adaptation mechanisms can be applied leading to agile and changeable production systems. Among these, adapting the degree of automation with respect to changeover times and high investment costs is one of the most challenging mechanisms. However, not only long-term changes, but also short-term adaptations can lead to enormous potentials, e.g. when night shifts can be supported by robots and thus higher labor costs and unfavorable working conditions at night can be avoided. These changes in the degree of automation on an operational level are referred to as fluid automation, which will be defined in this paper. The mechanisms of fluid automation are presented together with a case study showing its application on a disassembly station for electrical drives.

Cognitive abilities allow robots to learn and reason from their environment. The gained knowledge can then be incorporated into the robot’s actions which in turn affect the environment. Therefore, a cognitive robot is no longer a static system that performs actions based on a pre-defined set of rules but a complex entity that dynamically adjusts over time. With this, challenges arise for production systems that need to observe and ideally anticipate the cognitive robot’s behavior. Often, digital twins are employed to test and optimize production control systems. This paper presents a generic approach to characterize, model and simulate learning processes and formalized knowledge in hybrid production systems assuming different station types with learning effects. Thereby, quantitative and qualitative learning processes are mapped including knowledge sharing and transfer across entities. A modular and parameterizable design enables the adjustment to different use cases. Eventually, the model is instantiated as a digital twin of a real production system for product disassembly employing cognitive-autonomous robots among human operators and rigidly automated machines. The model shows great potential to be integrated into test beds for planning and control systems of cognitive factories.

Multinational companies deal with production processes in various countries by operating global production networks. These production processes are allocated to production plants with different levels of autonomy regarding strategic and operative decisions. Typically, each plant and the whole network are managed by one or more network managers who have to deal with a decision overload in their daily business. 50% of their decisions are made in less than 9 minutes and only a small amount of decision tasks are dealt with for more than one hour. To reduce this dilemma, it was found that the distribution of decision autonomy can be enhanced. It depends on the company's strategy and complexity dimensions in global production networks. However, so far there is little evidence on how to better distribute decision autonomy in global production networks in detail. Furthermore, it is not transparent at what level of centralism a global production network should be managed without cutting the capabilities of production plants. This paper presents a methodology, which examines relevant strategy dimensions and derives guidance on how to distribute decisions in global production networks. First, the network and production strategies of global production networks are classified. Second, relevant complexity dimensions and decisions are introduced. Third, the influence of the distribution of decision autonomy on strategy dimensions is quantified by an impact model. Furthermore, the effect of complexity on the distribution of decision autonomy is quantified by an impact model. Here, the integration of empirical data was used to validate the different influences. Finally, the ideal distribution of decision autonomy for specific production plants in the global production network is derived. The methodology is applied in an industrial use case to prove its practical impact.

Due to increasing demand for unique products, large variety in product portfolios and the associated rise in individualization, the efficient use of resources in traditional line production dwindles. One answer to these new challenges is the application of matrix-shaped layouts with multiple production cells, called Matrix Production Systems. The cycle time independence and redundancy of production cell capabilities within a Matrix Production System enable individual production paths per job for Flexible Mass Customisation. However, the increased degrees of freedom strengthen the need for reliable production control systems compared to traditional production systems such as line production. Beyond reliability a need for intelligent production within a smart factory in order to ensure goal-oriented production control under ever-changing manufacturing conditions can be ascertained. Learning-based methods can leverage condition-based reactions for goal-oriented production control. While centralized control performs well in single-objective situations, it is hard to achieve contradictory targets for individual products or resources. Hence, in order to master these challenges, a production control concept based on a decentralized multi-agent bidding system is presented. In this price-based model, individual production agents - jobs, production cells and transport system - interact based on an economic model and attempt to maximize monetary revenues. Evaluating the application of learning and priority-based control policies shows that decentralized multi-agent production control can outperform traditional approaches for certain control objectives. The introduction of decentralized multi-agent reinforcement learning systems is a starting point for further research in this area of intelligent production control within smart manufacturing.

Ever increasing demand for individualized and customized products induce the need for high variability in production and manufacturing through Mass Customisation. Mass Customisation requires more flexibility and adaptability capabilities in production systems. Matrix Production is a tact free job-shop like production system enabling variable production routing through a matrix shaped layout of partially redundant machines. Hence, it is one way to increase a production system's flexibility and adaptability. A more powerful production control system comes hand in hand with the evolution towards a tact free Matrix Production System. However, the additional degree of freedom due to the flexibility not only touches production control, but also production planning, thus enabling the production of portfolio external products. Implementation of a Product Generation Module optimizes the workload of Matrix Production Systems to increase their efficiency by assessing the suitability of co-production of portfolio external products. Generation of suitable production orders increase machine utilization without impeding the original multi-dimensional production goals. Thus, reaching new production strategies that include the creation of value through effective manipulation of minor products and byproducts. The flexibility of Matrix Production Systems acts as the Product Generation Modules enabler, insofar as flexibility is the ability of a system to perform within an acceptable production corridor without layout and planning adjustments. This can be enhanced by making use of the Matrix Production Systems adaptability to increase the set of portfolio external products through layout and planning adjustments. Hence, this strategy leads to a continuous automated planning phase and additional revenue due to the additional manufacture of minor products within a Matrix Production System. Doing so allows the Matrix Production System to react towards external demand related and internal capacity related events without sacrificing precious value creation opportunities. Ş 2020 Elsevier B.V.. All rights reserved.

Manufacturing companies operating in global production networks face rising complexities and increasing susceptibilities to disruptions. For coping with disruptions, companies are in need of a holistic, comprehensive disruption management, involving all network actors to find optimal measures. However, today?s disruption management approaches are characterized by intuitive, experienced-based reactions, limiting themselves to solely the production or the logistics perspective and hence not permitting an overarching reaction. Therefore, this paper presents an integrated approach to disruption management, combining the production and logistics perspectives. It incorporates DoE and metamodeling methods in a simulation model to enable efficient, robust decision-making in highly complex environments.

As intelligent Data Acquisition and Analysis in Manufacturing nears its apex, a new era of Digital Twins is dawning. Foresighted Digital Twins enable short- to medium-term system behavior predictions to infer optimal production operation strategies. Creating up-to-the-minute Digital Twins requires both the availability of real-time data and its incorporation and serve as a stepping-stone into developing unprecedented forms of production control. Consequently, we regard a new concept of Digital Twins that includes foresight, thereby enabling situational selection of production control agents. One critical element for adequate system predictions is human behavior as it is neither rule-based nor deterministic, which we therefore model applying Reinforcement Learning. Owing to these ever-changing circumstances, rigid operation strategies crucially restrain reactions, as opposed to circumstantial control strategies that hence can outperform traditional approaches. Building on enhanced foresights we show the superiority of this approach and present strategies for improved situational agent selection.

In this work an experimental study of the turning of AISI4140 is presented. The scope is the understanding of the workpiece microstructure and hardness-depth-profiles which result from different cutting conditions and thus thermomechanical surface loads. The regarded input parameters are the cutting velocity (vc = 100, 300 m/min), feed rate (f = 0.1, 0.3 mm), cutting depth (ap = 0.3, 1.2 mm) and the heat treatment of the workpiece (tempering temperatures 300, 450 and 600?C). The experimental data is interpreted in terms of machining mechanisms and material phenomena, e.g. the generation of white layers, which influence the surface hardness. Hereby the process forces are analyzed as well. The gained knowledge is the prerequisite of a workpiece focused process control.

Matrix production refers to a highly flexible production system based on independent production cells that are linked by a flexible transportation system. The production control system decides on the sequence of the production steps of each order and their allocation to specific time slots on the available machines. This paper presents an approach based on deep Q-learning that is able to cope with the dynamic events of the system. The performance of the machine learning-based production control is compared to a static rule-based approach. Additionally, the effects of coordination between the independent agents on throughput time is shown.

In today’s business environment, the trend towards more product variety and customization is unbroken. Due to this development, the need of agile and reconfigurable production systems emerged to cope with various products and product families. To design and optimize production systems as well as to choose the optimal product matches, product analysis methods are needed. Indeed, most of the known methods aim to analyze a product or one product family on the physical level. Different product families, however, may differ largely in terms of the number and nature of components. This fact impedes an efficient comparison and choice of appropriate product family combinations for the production system. A new methodology is proposed to analyze existing products in view of their functional and physical architecture. The aim is to cluster these products in new assembly oriented product families for the optimization of existing assembly lines and the creation of future reconfigurable assembly systems. Based on Datum Flow Chain, the physical structure of the products is analyzed. Functional subassemblies are identified, and a functional analysis is performed. Moreover, a hybrid functional and physical architecture graph (HyFPAG) is the output which depicts the similarity between product families by providing design support to both, production system planners and product designers. An illustrative example of a nail-clipper is used to explain the proposed methodology. An industrial case study on two product families of steering columns of thyssenkrupp Presta France is then carried out to give a first industrial evaluati

Industry 4.0 is increasingly finding its way into production. New technologies and instruments are increasingly changing production processes and, in particular, production work. New instruments to support employees make it possible to increase labour productivity, which is a key factor contributing to economic growth. While at the beginning the benefits were unclear and the investment strategy was missing, today the lack of acceptance and unsuitable organizational structures in the companies are the biggest obstacles. This is reminiscent of the first failure of Lean Management. Only after several years with the anchoring of Lean principles as a philosophy and a sustainable improvement culture, Lean Management was successful. What is needed is an approach that involves employees in incremental process improvements using Industry 4.0 in order to support the acceptance. To develop this approach, the respective success factors of Lean Management and Industry 4.0 are first studied and then combined to form an integrated process optimization approach. The result is a human-centred optimization approach that promotes an increased acceptance of Industry 4.0 and supports employees in coping with future flexible work content.

Due to excess of resource consumption, circular economy (CE) aims to return products to the production life cycle in an economically and ecologically reasonable way. Yet, few approaches focus on the strategic and network level of CE. First, existing approaches regarding the configuration of CE networks and the development of appropriate business models are reviewed. Sec- ond, an approach on how to integrate both aspects is presented. By integrating these aspects, implemen- tation strategies for CE in global production networks shall be developed facilitating strategic decisions. The approach is planned to be demonstrated in a German company supplying the automotive sector.

A network can be very beneficial for root cause analysis due to different data from various factories. Nevertheless, it is difficult to obtain reliable and consistent data. In this context, this paper aims to develop a method for data-driven oriented quality analytics of screwing processes considering a global production network.

Lean Management focusses on the elimination of wasteful activities in production. Whilst numerous methods such as value stream analysis or spaghetti diagrams exist to identify transport, inventory, defects, overproduction or waiting, the waste of human motion is difficult to detect. Activity recognition attempts to categorize human activities using sensor data. Human activity recognition (HAR) is already used in the consumer domain to detect human activities such as walking, climbing stairs or running. This paper presents an approach to transfer the human activity recognition methods to production in order to detect wasteful motion in production processes and to evaluate workplaces. Using sensor data from ordinary smartphones, long-term short-term memory networks (LSTM) are used to classify human activities. Additional to the LSTM-network, the paper contributes a labeled data set for supervised learning. The paper demonstrates how activity recognition can be included in learning factory training starting from the generation of training data to the analysis of the results.

Today’s success of industrial companies is largely determined by engineering competence and the digitization of all corporate processes. The design process and know-how of engineers is strongly individual and a rule-based description of their approach can often not be done at all or only with high effort. Existing knowledge can therefore only be passed on to other engineers with difficulty, which in particular increases the effort required for familiarisation. A further problem is the lack of an overview of existing components within a company, which very often leads to multiple designs and unnecessary waste of time for the engineer. The aim of this approach is to extract the implicit knowledge from existing CAD models with the aid of machine learning methods and thus to make it formalizable. In addition, a suitable classification and similarity analysis should quickly point out existing components. For this purpose, an AI-based assistance system is to be created. Based on the existing database, the assistant first points out to the engineer already existing, but very similar components. For that, the component type currently in construction firstly is identified and then very similar components are searched within the detected scale that are finally suggested to the engineer. The engineer now only has to parameterize the proposed components according to his application. In a further step, the assistant should also be able to suggest useful next design steps, which it has learned on the basis of the CAD data already available and their design history. The implicit experience knowledge that is contained in the existing CAD models thus ensures a design suitable for production and the avoidance of errors in the design.

Cyber Physical Production Systems (CPPS) provide a huge amount of data. Simultaneously, operational decisions are getting ever more complex due to smaller batch sizes, a larger product variety and complex processes in production systems. Production engineers struggle to utilize the recorded data to optimize production processes effectively because of a rising level of complexity. This paper shows the successful implementation of an autonomous order dispatching system that is based on a Reinforcement Learning (RL) algorithm. The real-world use case in the semiconductor industry is a highly suitable example of a cyber physical and digitized production system.

Fibre-reinforced plastics have been used for several years in various industrial sectors, such as aviation and the automotive industry, due to their low weight and good mechanical properties. Sheet Moulding Compound is a material that has been known since the 1960s and is used in automotive construction because of its good surface properties. To increase the mechanical properties, the well-known glass fibre sheet moulding compound is locally reinforced with unidirectional carbon fibre sheet moulding compound. In this way, partially higher mechanical properties can be achieved. However, the combination of materials also leads to a large number of defects, such as the inclusion of foreign bodies, which must be avoided. Therefore, a quality assurance system must be developed which quickly detects a large number of different defects. The method of data fusion is suitable for this purpose. This article explains in more detail how complete quality assurance can be achieved with the aid of laser light sectioning and active thermography by data fusion.

Enabled by the development of internet technologies, cyber-physical production systems (CPPS) are expected to open up entirely new possibilities to improve the efficiency of existing assembly systems of industrial companies. Nevertheless, realizing the potential of CPPS still remains a difficult task for small and medium-sized enterprises (SME), given the high variety of improvement possibilities offered by CPPS enabling technologies and the limited resources for their deployment. Hence, it is necessary to develop an implementation strategy of CPPS. Meanwhile, the consideration of location factors could support industrial companies to identify the appropriate CPPS implementation strategy since the location factors highly effect assembly system environment. In this context, a new approach to analyse the influence of location factors on the implementation of CPPS is exposed in this paper, which aims at investigating and identifying of relationships in between. Firstly, an application map of CPPS is generated. Secondly, the manufacturing industry status analyzed and subsequently a catalog of currently important location factors for the assembly systems are identified. Then a qualitative model of a relational analysis is established by an agglomerative hierarchical clustering algorithm. An industrial case study is used to demonstrate the applicability and the validity of the proposed approach.

Micro-transmissions, consisting of micro-gears with a module <200µm, are used in manifold industrial applications, e.g. the medical industry. Due to the technological limits of their manufacturing processes, micro-gears show large shape deviations compared to their size, which significantly influence their lifetime. Thus, for micro-gears a model has been developed to enable a prognosis of their lifetime based on areal measurements of the gear geometry, finite elements simulations as well as lifetime experiments. To significantly reduce the amount of experiments, existing prior knowledge is additionally used as input to the lifetime model by means of Bayesian statistics. To enable a time-efficient application of the model for industrial series production, in this article the application of a machine learning approach based on artificial neural networks is investigated. The uncertainty of the model is evaluated according to the principles of the Guide to the Expression of Uncertainty in Measurement (GUM).

Production Management is an important issue for organizations that spend considerable amounts of investment annually on personnel training. Especially in the era of Industry 4.0 and Intelligent Manufacturing, considering the exponential growth of new knowledge and information, personnel need to update and supplement the necessary knowledge. Nevertheless, there is a lack of adequate methodology for executing trainings in the field of production management. This paper aims to develop a method for executing production management training which combines online learning and offline training as well as practical parts by using an Industry 4.0 Innovation Center equipped with model devices. A procedure is to first starting with an E-Learning module containing basic knowledge, accessible on the Learning Platform Moodle. Secondly, an on-line survey is created to collect expectations and requirements. Then the training schedule is carried out for execution of professional training. The training part in the innovation center will contribute to build up the basis for adaptions of the training knowledge to practical need of a company. Lastly the test and evaluation is conducted via virtual team room (Vitero). A case study based on training service provider is used to validate the feasibility of the approach. The derived results are presented and conclusions are discussed.

The serial application of a new technology requires a positive monetary valuation of the technologies overall costs including the development project and manufacturing benefits. The endeavor of planning and therefore also assessing an immature technology's serial application is severely hampered by strong advances in the technology's development. In most cases, previous research has not taken future stages of development into account. Hence, this paper aims at assessing and planning an immature technology's serial application under consideration of future stages of development. The methodology shall be introduced using the example of the additive manufacturing process of selective laser melting (SLM). For the purpose of reaching this objective, a cost model supporting the planning process shall be elaborated and combined with a scenario analysis for forecasting future technological development.

When an assembly line experiences downtime, it incurs both financial and productivity costs, in addition to environmental costs resulting from ineilicient or ineffective uses of resources. Material is wasted in the form of scrapped work in progress (WIP), and enery is wasted in powering the machines and facilities while the line is restored to an operational state. This work performs an analysis of key periormance indicators (KPls) to investigate their potential impacts in maximizing the uptime of a simulated assembly line with automation and quality inspection. Previous work has not considered the linkages between baseline KPls. The interdependencies and effects of baseline KPls such as preventative maintenance time, corrective maintenance time, time to failure, and others are explored in order to analyze the production system on a more granular Ievel. The results of this work inform production planning efforts and enable more eflective and sustainable operation.

Due to today’s rapidly changing trends, global supply chains have to face complex challenges especially concerning sustainability aspects like climate change and scarcity of natural resources. Established supply chain performance measurement systems (SCPMS) neglect the impact of those factors. This paper aims at providing an approach for an SCPMS including performance measures with sustainable relevance to include the trends mentioned above. Based on state-of-the-art SCPMS and sustainability key performance indicators focusing on ecological aspects, an integrated method to strategically control global supply chains is developed. A set of metrics is presented and its qualitative interdependencies are discussed.

In recent years, European manufacturing companies are gradually applying innovative PSS (Product Service Systems), as strategic opportunity for differentiating from competitors, offering an integrated bundle of products and services, targeted on specific needs of different customers. At the same time, frugal innovation has also surged as a new business concept based upon an intelligent use of resources to fulfill region-dependent customers’ needs. Both approaches bring forth rethinking of established business models, which in turn asks for an in-depth analysis of the implications on the company organization and infrastructure, at supply chain and plant levels, urging towards manufacturing networks and reconfigurable assembly lines. This paper presents a formalized framework to support product-service design and the related business model characterization, in the context of frugal innovation. The methodology is applied to three real industrial scenarios respectively in the aeronautics, the domestic appliances and the machinery industry, which are analyzed within the framework of the H2020 European funded project ‘ProRegio’.

The integration of sheet molding compound (SMC) as discontinuous fiber reinforced plastics (DiCoFRP) and unidirectional fiber reinforced tapes (UD-Tape) as continuous fiber reinforced plastics (CoFRP) aims to provide a novel cost-effective hybrid material with better mechanical properties. For the handling of the combined CoDiCo-semi-finished part, the reliable gripping during the overall process chain is important. For complex 2.5D contours, the combination of preforming technology and handling technology is worthwhile. In order to combine both technologies, the separately consideration of handling and preforming technology is necessary. This study considers on one hand the necessity of the preform step for CoDiCo-semi-finished parts, on the other hand the possibility to integrate the UD-tape with SMC. Moreover, the quality of the preformed semi-finished parts effects directly on mechanical properties of final parts, the quality assurance system is therefore necessary, in order to ensure a defect free product during preforming step and to guarantee fast reaction, in case any defects are detected. One objective of this project is to generate methods for holistic quality assurance during manufacturing of 3D SMC parts with integrated unidirectional-fibers. Therefore, sensor systems, thermography, ultrasound and acoustic methods will be used.

An increasingly uncertain, customer-centric, and dynamic environment nowadays challenges manufacturing companies on a global scale. To handle this challenge, enterprises are distributing their production in global production networks. To deal with the growing demand for individualization, companies need to diversify their product portfolio. This leads to a growing number of production ramp-ups. Large companies are used to production ramp-ups on a global scale and have developed established tools and methods to optimize ramp-ups. Small and medium-sized enterprises (SME), however lack a consistent and efficient methodology to deal with global production ramp-ups. For this reason, this article presents a practice-oriented methodology for efficiently managing the production ramp-up at different production sites. The methodology consists of three elementary phases: the analysis of the target system and relevant influencing factors, the planning of different phases in the production ramp-up, and the integration of a disruption management model to robustly control ongoing production ramp-ups. For testing its practical suitability, the procedure is exemplarily applied to the production ramp-up of a device for engine management in the automotive supplier market at different sites worldwide.

In der heutigen Zeit stehen produzierende Unternehmen aufgrund der Unsicherheit und Komplexität von Umwelteinflüssen sowie des wachsenden Wettbewerbsdrucks vielen Herausforderungen gegenüber. Die Pandemie hat uns deutlich veranschaulicht, wie volatil und fragil unsere Lieferketten geworden sind. Eine Möglichkeit, diese Herausforderungen gemeinsam zu überwinden, liegt in der Kollaboration mit anderen Unternehmen des Wertschöpfungsnetzwerkes. Kollaborationen, also die erfolgreiche Zusammenarbeit mit strategischen Partnern und Kunden zur Erreichung gemeinsamer Ziele, werden weiter an Bedeutung gewinnen. An-statt einzelner Unternehmen werden zukünftig daher ganze Wertschöpfungsketten und -netzwerke im Wettbewerb zueinanderstehen. Das bedingt einen Wandel hin zu einem schnellen und nahtlosen Datenaustausch zwischen den Akteuren im Wertschöpfungs-netzwerk. Die fortschreitende Digitalisierung und damit eine allgemein immer stärker vernetzte Welt unterstützen derartige Kollaborationen zu-nehmend, da das Teilen und die gemeinschaftliche Nutzung von Daten deutlich vereinfacht werden. Gleichzeitig wird der richtige Umgang mit Daten wettbewerbsentscheidend sein. Die Digitalisierung wird vom Wandlungstreiber zum Wandlungsbefähiger. Durch innovative Geschäftsmodelle und das Aus-schöpfen des in Daten verborgenen Potenzials lässt sich eine verlässliche, flexible und gleichzeitig ressourcenschonende Wert-schöpfung verwirklichen. Der Wirtschafts- und Wissenschaftsstandort Deutschland muss hier eine Führungsrolle einnehmen, um langfristig den heutigen Wohlstand zu erhalten. Die Menge an vorhandenen, cloudbasierten Kollaborationsplattformen wächst dabei stetig. Insbesondere kleine und mittlere Unter-nehmen müssen viele verschiedene Kundenplattformen gleichzeitig bedienen, während sie selbst noch mit internen Digitalisierungs-herausforderungen kämpfen. Standardisierungsinitiativen für sichere Datenräume in der Industrie, wie GAIA-X, bergen deshalb ein großes Potenzial. Zusätzlich zu diesen grundlegenden infra-strukturellen Fragestellungen bestehen weitere Herausforderungen bezüglich Kollaborationsvorhaben. Eine besonders große Bedeutung wird dabei dem souveränen Umgang mit Datenschutz und Datensicherheit zu Teil. Oftmals bestehen Vorbehalte, dass durch die Preisgabe von Daten und Informationen mühsam erarbeitetes Know-how und kontinuierlich aufgebaute Wettbewerbsvorteile verloren gehen. Gleichzeitig können Anwender:innen aus einem ingenieurswissenschaftlichen Umfeld die Risiken digitaler Kollaboration jedoch nur bedingt einschätzen. Um die eigene Wettbewerbsposition nachhaltig zu sichern müssen deshalb digitale Kompetenzen aufgebaut und Kollaborationshemmnisse überwunden werden. Einen wichtigen Impuls zur Umsetzung erfolgreicher Kollaborationsvorhaben können Erfolgsgeschichten und klare Handlungsempfehlungen geben, die aufzeigen, wie Kollaborationen in der Praxis konkret angegangen werden können und welcher Mehrwert aus ihnen erwächst. Deshalb möchten wir mit dem vorliegenden Handlungsleitfaden produzierenden Unternehmen eine solche Orientierungshilfe geben. Die nachfolgend erläuterten Kollaborationsprojekte und abgeleiteten Best Practices sollen helfen eigene Strate-gien auf dem Weg zu mehr Kollaboration zu finden. Wir wünschen Ihnen viel Freude beim Lesen und stehen Ihnen für Fragen und Diskussionen jeder Zeit zur Verfügung.

In today's world, manufacturing companies face many challenges due to the uncertainty and complexity of environmental influences as well as increasing competitive pressures. The pandemic has clearly illustrated how volatile and fragile our supply chains have become. One way to overcome these challenges together is to collaborate with other companies in the value network. Collaborations, i.e. successful cooperation with strategic partners and customers to achieve common goals, will continue to gain in importance. Instead of individual companies, entire value chains and networks will therefore compete with each other in the future. This will require a shift toward fast and seamless data exchange between the players in the value network. Advancing digitization and thus a generally increasingly networked world are increasingly supporting such collaborations, as the sharing and collaborative use of data is becoming much simpler. At the same time, the right handling of data will be decisive for competition. Digitization is moving from being a driver of change to an enabler of change. Innovative business models and the exploitation of the potential hidden in data will make it possible to realize reliable, flexible and, at the same time, resource-conserving value creation. The number of existing cloud-based collaboration platforms is growing steadily. Small and medium-sized enterprises in particular have to serve many different customer platforms at the same time, while they them-selves are still struggling with internal digitization challenges. Standardization initiatives for secure data rooms in the industry, such as GAIA-X, therefore hold great potential. In addition to these fundamental infrastructural issues, there are further challenges with regard to collaboration projects. Particular importance is attached to the competent handling of data protection and data security. There are often reservations that the disclosure of data and information will result in the loss of hard-earned expertise and competitive advantages that have been built up over time. At the same time, however, users from an engineering environment are only able to assess the risks of digital collaboration to a limited extent. In order to secure one's own competitive position in the long term, digital competencies must therefore be built up and barriers to collaboration overcome. Success stories and clear recommendations for action can provide an important impetus for the implementation of successful collaboration projects, showing how collaborations can be approached in practice and what added value they generate. That is why we would like to provide manufacturing companies with such guidance in the form of this action guide. The collaboration projects explained below and the best practices derived from them are intended to help companies find their own strategies on the path to more collaboration. We hope you enjoy reading this guide and are always available for questions and discussions

An increasing desire for individualization and a greater customer focus drive companies to produce more individualized products that go beyond the limits of mass customization, thus initiating the MPP. The high variability of personalized products leads to an intensification of the VUCA challenges (volatility, uncertainty, complexity, ambiguity), so that new approaches and tools for designing and operating GPNs have to be found. To support the development of appropriate concepts, a deeper understanding of the influence of MPP on the planning decisions of GPNs has to be gained. Since no systematic and holistic approaches exist in the literature so far, this contribution to the book aims at developing a framework to analyze the implications of MPP for the different tasks in designing and managing GPNs. The second goal of the contribution is to identify appropriate concepts that address the implications of MPP. There is no claim to completeness. Rather, it is intended to demonstrate how the framework supports the identification of suitable concepts. Furthermore, it is intended to provide a starting point and guiding structure for further research in the area of the design and management of GPNs in the era of mass personalization.

A key challenge for manufacturing companies today is to ensure overall process quality within their production network while working in globally distributed and dynamic environments. In this chapter, a description model to systematically analyze process quality across locations and identify improvement measures using a value stream-based approach is presented. In order to holistically increase process quality in the network, two evaluation procedures based on a hierarchical key performance indicator system are discussed. This method is especially useful in production networks, where certain products are manufactured in several steps across multiple plants.

Enforced by continuously expanding production structures and production programs, original equipment manufacturers have faced an increasing complexity when dealing with product allocation decisions in recent years. Fluctuations in demand and other key omponents of the production network require adaptable and well-structured production mechanisms to maintain and enhance global competitiveness. Questions of where and when to produce certain products have risen in priority, especially in the context of lobally operating production networks, due to extended factor costs and global market dynamics. Therefore, it is essential for manufacturers to further optimize and reconfigure their production networks as historically grown networks or isolated allocation decisions have led to efficiency losses. The problems of product allocation and network configuration are highly interdependent and hence need to be taken into account in an integrated manner when making decisions. This chapter proposes several approaches that particularly focus on product allocation decisions, whereas some integrated approaches also regard configurational aspects. The presented decision support methods in this chapter range from simpler tools that help comparing the most promising allocation and reconfiguration decisions (such as the portfolio approach) to more complex and elaborate methods that aim to provide an optimal solution for product allocation (e.g., mathematical optimization).

The desire for individual customer solutions is rising in the manufac-turing industry. The digitalization enables new forms of creating customer value, but simultaneously opens up the market for new player from the tech industry, so that traditional production companies have to challenge their business models. The development of existing business models into digital business models is therefore of high strategic relevance to maintain a company's competitiveness. However, manufacturing companies are hesitant to adapt digital usiness models. For successfully building digital business models in manufacturing, their connec-tion with the production strategy must be considered. Since there are no ap-proaches that take these interactions into account, the goal of this paper is to de-velop an integrated approach to develop production strategy and digital business model simultaneously. For this purpose, two morphological boxes are developed to characterize production strategy and digital business model. Their interde-pendencies were assessed in an expert interview.

Enforced by continuously expanding production structures and production programs, original equipment manufacturers have faced an increasing complexity when dealing with product allocation decisions in recent years. Fluctuations in demand and other key omponents of the production network require adaptable and well-structured production mechanisms to maintain and enhance global competitiveness. Questions of where and when to produce certain products have risen in priority, especially in the context of lobally operating production networks, due to extended factor costs and global market dynamics. Therefore, it is essential for manufacturers to further optimize and reconfigure their production networks as historically grown networks or isolated allocation decisions have led to efficiency losses. The problems of product allocation and network configuration are highly interdependent and hence need to be taken into account in an integrated manner when making decisions. This chapter proposes several approaches that particularly focus on product allocation decisions, whereas some integrated approaches also regard configurational aspects. The presented decision support methods in this chapter range from simpler tools that help comparing the most promising allocation and reconfiguration decisions (such as the portfolio approach) to more complex and elaborate methods that aim to provide an optimal solution for product allocation (e.g., mathematical optimization).

This chapter explores the use of operations research methods in production network managment. Challenges like increasing product variety, the fragmentation of value streams, and other have made the use of OR methods necessary. The chapter provides an overview of the commonly used methods in this context and discusses typical applications in production network managment. Furthermore, the benefits of applying OR methods in production networks like increased understanding and the ability to solve complex problem with conflicting goals are explored. The limitations of these methods are recognized and elaborated as well. Finally, a brief outlook on future developments in this field is given.

Increasing importance of X-Ray Computed Tomography (CT) for industrial applications demands suitable approaches for user support. These are intended to guide the choice of setting parameters to improve measurement quality and enable CT-technology access also to non-experts. In the past, several user support systems (USS) have been developed. One promising approach uses knowledge gained from historical measurements. However, this initially requires time-consuming measurements and thus limits generalization, and the potential of machine-learning (ML) techniques. Further, no statement about the achieved quality is possible. In this paper, a concept and the required workflow to build a USS using ML is introduced. Therefore, a suitable ML approach is identified by examining patterns between ML algorithms and their characteristic applications. To provide the required database and analyze the measurement quality, the use of a virtual CT is suggested. Based on the proposed concept, future work will focus on the implementation of the USS.

Als initiales Werkzeug zur Identifikation konkreter Digitalisierungsprojekte sowie zur regelmäßigen Einordnung des bereits erreichten Ist-Zustandes versteht sich der Leitfaden „Antriebstechnik 4.0“ als kontinuierlicher Wegbegleiter und Impulsgeber im Zuge der digitalen Transformation der Branche. In Zeiten des disruptiven technologischen Fortschritts mit ebenso großen Handlungsbedarfen soll der Leitfaden „Antriebstechnik 4.0“ Unternehmen als Anstoß und Orientierung auf ihrem spezifischen Weg hin zur „antriebstechnischen Exzellenz“ dienen.

Die Automobilindustrie steckt in einem Transformationsprozess un-geahnten Ausmaßes und Ausgangs. Ob durch striktere europäische Abgasgrenzwerte, den Zwang lokaler Emissionsfreiheit oder den Druck des chinesischen Marktes beim Kampf um eine neue Vorherrschaftsrolle - die Gründe deutscher Automobilisten zur Elektrifizierung sind vielschichtig und die Folgen kaum abschätzbar. Die Frage, ob neue Antriebstechnologien in den Markt eingeführt wer-den, stellt sich mittlerweile kein Automobilhersteller mehr, stattdessen verbleibt die Frage nach dem ?wie?. Mit der diesjährigen wbk Herbsttagung ?Auf dem Weg zur Elektromobilität ? Wettbewerbsfaktor Produktionstechnik? wollen wir die vorhandenen Chancen im Bereich der Produktionstechnik für die Elektromobilität aufzeigen und einen Beitrag dazu leisten, dass diese auch genutzt werden. Hochkarätige Impulsvorträge aus Industrie und Forschung schaffen die Diskussionsbasis für einen Informationsaustausch zur Elektromobilität. Die wbk-Herbsttagung bietet dabei eine Plattform für den Dialog zwischen Politik, Anwendern, Produzenten, Anlagenbauern sowie dem wbk als Forschungspartner vor Ort.

Einflussfaktoren und Wandlungstreiber lassen sich identifizieren und klassifizieren. Das ist die gute Nachricht. Die schlechte: Das ist nicht ohne Aufwand zu haben. An erster Stelle steht die Frage, woher die identifizierten Wandlungstreiber kommen - ...

Die Entscheidungstheorie ist eine Wissenschaft. Deshalb kann es nicht verwundern, dass es für komplexe Entscheidungsprobleme auch komplexe, wissenschaftliche Lösungsansätze gibt. Einer dieser Ansätze ist die multikriterielle Optimierung, die im folgenden Abschnitt in groben Zügen vorgestellt wird.

In Folge der Globalisierung und des verschärften Wettbewerbs suchen kleine und mittlere Unternehmen (KMUs) kontinuierlich nach Möglichkeiten zur Kostensenkung. Der Fokus der unternehmerischen Aktivitäten rückt dabei zunehmend auf ihre Kernkompetenzen. Gleichzeitig steigt die strategische Bedeutung von Einkauf und Beschaffung. Aufgrund der globalen Vernetzung der Wirtschaftsräume versuchen viele Unternehmen durch Beschaffung in Niedriglohnländern weitere Kostensenkungspotentiale zu realisieren. Die Herausforderungen bei der Lieferantequalifizierung und -entwicklung, insbesondere drohende Qualitätseinbußen und ein erhöhter Koordinationsaufwand, sind dabei jedoch nicht zu vernachlässigen. Daher sind potentielle Lieferanten einer umfassenden Bewertung zu unterziehen, um über die Vorteilhaftigkeit der Lieferantenqualifizierung kontinuierlich entscheiden zu können. Bestehende Ansätze zur Lieferantenbewertung dienen der einmaligen Beurteilung und Entscheidungsfindung in Sourcingprojekten. Sie berücksichtigen jedoch keine dynamischen Entwicklungen und Risiken. Mit dem Leitfaden wurde eine neue und umfassende Methode zur systematischen Planung und Durchführung von Sourcingprojekten entwickelt. Der Leitfaden unterstützt Un-ternehmen bei sämtlichen projektrelevanten Schritten, von der IST-Analyse bis hin zur Entscheidung über Lieferantenentwicklungsmaßnahmen. Marktdynamiken und Risiken werden ebenfalls integriert, um dynamisch auf veränderte Umfeldeinflüsse reagieren zu können. Durch die Anwendung des Konzepts der FQS strukturieren Unternehmen den Aufwand einer Lieferantenentwicklung und entscheiden nach bestimmten Projektphasen über die Projektfortführung. Dazu stehen den Unternehmen zwei in MS Excel® umgesetzte Softwarefunktionsmuster zur Verfügung, die die Anwendung in der Praxis erleichtern.

Sustainable individual mobility can only be achieved by reducing the energy consumption and consequently the CO2 emissions. Solutions therefore can be found by using lightweight materials which lead to a reduction of the moving mass of cars. To exploit the entire potential of lightweight design, Fiber Reinforced Plastics (FRP) are more and more considered by the automotive industry. However, due to the current low automation rate and high production costs especially Carbon-Fiber-Reinforced Plastics (CFRP) are not widely used in high volume production.
An essential step towards an industrialization of the production process of CFRP is the implementation of a capable quality assurance strategy into the process technology. Here especially the draping-process - the forming operation of semi-finished textiles - has to be considered, because of the multiple imperfections which can occur here.
This paper will provide an approach for the design of a measurement machine for quality assurance of preforms in the CFRP process chain. Thereby the requirements concerning the machine as well as the used measurement systems will be discussed.

Im globalen Wettbewerb kann nur bestehen, wer Spitzenprodukte zu wettbewerbsfähigen Preisen rasch in den Markt bringt. Ferner kommt es darauf an, sich auf sich ändernde Einflüsse einzurichten, beispielsweise neue Fertigungstechnologien, Schwankungen in den Stückzahlen oder in der Variantenzahl über den Produktlebenszyklus.
Dies bezeichnen wir als Robustheit. Weiterhin erhöht die Durchdringung der Produkte und Leistungserstellungsprozesse mit Informations- und Kommunikationstechnik die Komplexität der Produktentstehung. Im Zuge der Produktentstehung sind Abhängigkeiten der Domänen Mechanik, Elektronik/Elektrik und Software sowie zwischen Produkt- und Produktionssystementwicklung zu beachten. Heute finden diese Abhängigkeiten nur unzureichend Berücksichtigung. Die Folge sind aufwändige Iterationsschleifen im Entwicklungsprozess. Das Verbundprojekt VireS -Virtuelle Synchronisation von Produktentwicklung und Produktionssystementwicklung stellt sich dieser Herausforderung. Ziel war ein Instrumentarium zur integrativen Entwicklung von Produkt und Produktionssystem unter frühzeitiger Berücksichtigung der Aspekte Kosten und Robustheit.

Mikrozahnräder kommen vor allem als wesentlicher Bestandteil von Mikrogetrieben in verschiedensten Branchen, wie beispielsweise der Medizintechnik oder der Luft- und Raumfahrttechnik, zum Einsatz. Die Anforderungen an die Präzision und Leistungsfähigkeit dieser Mikrogetriebe steigen, wodurch der Qualitätssicherung und speziell der geometrischen Beurteilung der Mikrozahnräder eine verstärkte Bedeutung zukommt. In diesem Beitrag wird ein Mikroverzahnungsnormal vorgestellt, mit dem experimentell die Messunsicherheit bei der Messung von Mikrozahnrädern ermittelt werden kann.

Mobilität ist ein wesentliches Merkmal des modernen Menschen. Sie gibt ihm persönliche Freiheit und erhöht seine Lebensqualität. Sie ist einerseits Basis seines wirtschaftlichen Handelns, macht ihm Güter aus aller Welt zugänglich und fördert seinen Wohlstand. Sie ermöglicht ihm andererseits soziale Begegnungen und bereichert seine Erlebniswelt. Dabei steigt das Bedürfnis nach Mobilität weltweit, was zu Herausforderungen hinsichtlich der Abhängigkeit von fossilen Brennstoffen und damit auch der Sicherung des Wirtschaftsstandorts Deutschland führt. Dies geht einher mit der Notwendigkeit, die Luftqualität zu sichern und die Lärmemissionen zu reduzieren, insbesondere in den Mega-Städten und Ballungszentren, in denen immer mehr Menschen wohnen.

Gerundete Aluminium-Strangpressprofile für leichte Tragwerksstrukturen produktflexibel und automatisiert zu bearbeiten, ist mit derzeitiger Maschinentechnik nur unter hohem technischen Aufwand möglich. Zur Flexibilisierung des Bearbeitungsprozesses wurde im Rahmen des Sonderforschungsbereiches Transregio 10 ein neuartiges Maschinenkonzept entwickelt und prototypisch umgesetzt. Der Schwerpunkt liegt dabei in der Integration von Handhabung und Bearbeitung in einem ganzheitlichen Ansatz. Um eine komplette, präzise und automatisierte Bearbeitung von dreidimensionalen Aluminium-Strangpressprofilen darstellen zu können, liegt der Fokus der bestehenden Arbeiten auf der Genauigkeitssteigerung der Maschinentechnik, der Integration ausgewählter Zusatzprozesse sowie dem Aufbau einer einfachen und effizienten Programmierumgebung. [3] Tekkaya, A.E.; Baier, H.; Biermann, D.; Fleischer, J.; Schulze, V.; Zäh, M.F.; Pietzka, D.: Integration von Urformen, Trennen und Fügen für die flexible Fertigung von leichten Tragwerksstrukturen - Der SFB/TR10, Ergebnisbericht der Phase II, Fortschritt - Berichte VDI, Reihe 2, Nr. 678, Düsseldorf: VDI Verlag 2011, ISBN 978-3-18-367802-0

One of the main challenges within the SFB/TR 10 process chain consists in handling and precise machining of variable formed profiles without changing over the jigs and fixtures. For this the profile contour as well as the spatial position and orientation of the profile have to be known. To provide this information, a component-specific scale for contour detection and precision posi-tioning of multi-dimensionally formed extrusion profiles was developed and realised. The scale is scribed onto the surface of the profile by a laser. To determine the contour, the scale is scanned using digital image processing and the profile contour is measured by a laser triangulation sensor. This article describes the general approach, the achieved measurement accuracies as well as the implementation of this approach within an automated process chain for the flexible production of space-frame structures.

Im Rahmen des Projektes Ogemo.net galt es, Methoden zur Nutzen- und Leistungsbewertung hybrider Produkte, also der Kombination aus Sach- und Dienstleistung, zu entwickeln [MEI-06, LUG-06]. Um die oben genannte Methode zur Prognose der Ausfall- und Instandsetzungskosten von produktionstechnischen Maschinen und Anlagen unter Berücksichtigung produktbegleitender Dienstleistungen zu entwickeln, anzuwenden und zu validieren, ist neben komplexen Berechnungsschritten eine breite Datenbasis notwendig. Daher wurde im Rahmen des Forschungsprojektes ein prototypisches Software-Tool entwickelt, das die Datenbasis mit den Berechnungsmethoden zusammenführt und automatisiert. Dieser sogenannte Servicekonfigurator stellt den Anwendern zwei wichtige Auswertungen zur Verfügung: zum einen eine Leistungsbewertung von produktbegleitenden Dienstleistungen und zum anderen ein Kalkulationsinstrument zur Berechnung von Garantie- und Servicekosten sowie den damit verbundenen Risiken. Produktbegleitende Dienstleistungen können nur dann erfolgreich vermarktet werden, wenn der Kunde dadurch einen Mehrwert erhält und dieser entsprechend quantifiziert werden kann. Hersteller und Betreiber von Anlagen und Maschinen erhalten mit dem Servicekonfigurator die Möglichkeit, die durch das Ausfallverhalten verursachten Kosten zu ermitteln und sie dem Nutzen aus Verfügbarkeitssteigerungen durch produktbegleitende Dienstleistungen gegenüberzustellen [VDI-86]. Durch diese Kosten-Nutzen-Analyse bietet das Software-Tool den Maschinenherstellern die Gelegenheit, ihre angebotenen Dienstleistungen strategisch zu platzieren [FLE-07a]. Neben der Entwicklung und Implementierung des Software-Tools galt es ferner, den Servicekonfigurator exemplarisch bei den Verbundpartnern anzuwenden und zu validieren. Die Konzeption sowie die Implementierung des Servicekonfigurators wird in den nachfolgenden Kapiteln dargestellt.

Zur genauen Bearbeitung räumlich gekrümmter Strangpressprofile ist die exakte Kenntnis der räumlichen Lage und Orientierung des zu bearbeitenden Profils innerhalb der Bearbeitungsmaschine zwingend notwendig. Zusätzlich erschweren Abweichungen der Ist- von der Soll-Profilkontur eine präzise Bearbeitung. Dieser Artikel stellt eine auf bauteil-immanenten Markierungen aufbauende Vorgehensweise zur Positionierung und Konturerfassung nahezu beliebig gekrümmter Profile vor. Ausgehend von der Zielsetzung werden die am Institut für Produktionstechnik (wbk) der Universität Karlsruhe (TH) erarbeiteten Ansätze und der daraus resultierende messtechnische Versuchsaufbau beschrieben. Der Aufbau einer anforderungsgerechten Markierungsgeometrie zur Positionierung und Konturerfassung wird hergeleitet. Abschließend werden erste Versuchsergebnisse vorgestellt. Spatially curved extrusion profiles can only be processed in accordance with high quality standards if the spatial position and orientation of the profile inside the machine tool are known. Any deviations of the profile geometry may also cause processing inaccuracies.Against this background, the article describes a procedure for the positioning and contour detection of almost any spatially curved tube profile based on component-specific markings. Beginning with the objective, the approaches elaborated at the Institute of Production Science (wbk) of the University of Karlsruhe (TH) and the procedure developed on the basis of these results are described. Subsequently, the first empirical results of segmential contour detection are illustrated. The article explains a method for the derivation of a marking geometry particularly suitable for the requirements of this application.

ProactAS steht für Proaktive Anlaufsteuerung entlang der Wertschöpfungskette. Es handelt sich um eine modulare Softwareplattform, die die Beteiligten eines Produktionsanlaufs vom Zeitpunkt der Planung der Anlagentechnik bis über das Erreichen der Kammlinie hinaus dabei unterstützt, Störungen frühzeitig zu erkennen und effiziente Maßnahmen zur Störungsbeseitigung einleiten zu können. Hierdurch soll einerseits ein früherer Markteintritt und andererseits eine Kostenreduktion realisiert werden. Oberste Prämisse ist der zielgerichtete und effiziente Einsatz der begrenzten Ressourcen, um bei aktuellen und prognostizierten Planabweichungen schnell undaufwandsarm gegensteuern zu können und damit eine signifikante Verkürzung des Anlaufs zu erreichen. Eigentlich für die Automobil- und Automobilzulieferindustrie entwickelt, ist jedes Softwaremodul für sich einsetzbar, so dass alle Module auch für andere Branchen nutzbar sind. Basis der Idee ist es, den Produktionsanlauf mit den neuen Anlagen, den Materialien und der Inbetriebnahmemannschaft als Regelkreis zu verstehen und das Personal zu befähigen, zu jeder Zeit sowohl die aktuelle als auch die zukünftige Situation des Anlaufes zu erkennen und ursachengerecht zu analysieren. Der Begriff „Produktionscockpit“ veranschaulicht plastisch die Gesamtfunktion. Zur Realisierung der Proaktiven Anlaufsteuerung wurden im Rahmen von ProactAS verschiedene Kern- und Unterstützungskomponenten entwickelt.