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Nicole Stricker

Dr.-Ing. Nicole Stricker

Bereich: Produktionssysteme
Sprechstunden: nach Vereinbarung
Raum: 111, Geb. 50.36
Tel.: +49 721 608-42444
Fax: +49 721 608-45005
Nicole StrickerStf9∂kit edu

Campus Süd

Dr.-Ing. Nicole Stricker

Forschungs- und Arbeitsgebiete:

  • Adaptive Produktionssysteme
  • Digitalisierungsstrategie
  • Maschinelles Lernen und Data Mining
  • Agile Fabrikplanung
  • Robuste, intelligente Produktionssteuerung


Allgemeine Aufgaben:

  • Vorlesungsbetreuerin der Vorlesung...
    • Global Production Engineering (Carl Benz School)
    • SmartFacoty@Industry (Carl Benz School)
    • Operations Management (Karlsruher School of Optics and Photonics)
    • Leadership 4.0


Dissertation: Robustheit verketteter Produktionssysteme: Robustheitsevaluation und Selektion des Kennzahlensystems der Robustheit



seit 01/2016 Oberingenieurin der Gruppe Produktionssystemplanung am Institut für Produktionstechnik (wbk) des Karlsruher Instituts für Technologie (KIT)
06/2015 Forschungsaufenthalt an der UC Berkeley (USA)
10/2011 - 12/2015 Wissenschaftliche Mitarbeiterin am Institut für Produktionstechnik (wbk) des Karlsruher Instituts für Technologie (KIT)
10/2005 - 07/2011 Studium des Wirtschaftsingenieurwesens am Karlsruher Institut für Technologie (KIT)
1986 Geboren in Aalen



[ 1 ] Lanza, G.; Stengele, G. & Stricker, N. (2012), „Improved Calculation of Weibull distributions for deficient industrial data in the context of Life Cycle Costs“. Towards Implementing Sustainable Manufacturing, Hrsg. Prof. Dr.-Ing. G. Seliger, S. 225-231.
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.

[ 2 ] Fleischer, J.; Lanza, G.; Appel, D.; Stricker, N.; Hennrich, H. & Herder, S. (2013), „Life Cycle Performance 4.0 - Strategische und technische Lösungen für den intelligenten Betrieb von Maschinen und Anlagen“, wt Werkstattstechnik online, Band 2, S. 124-129.
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.

[ 3 ] Lanza, G.; Stricker, N. & Appel, D. (2013), „Calculation of Maintenance Costs on Poor Data Basisand Implementation in Industrial Practice“. Product-Service Integration for Sustainable Solutions, Hrsg. Horst Meier, Springer, S. 597-608.
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.

[ 4 ] Lanza, G. & Stricker, N. (2013), „Reliability 2.0 - Challenges in Reliability of Future Production Systems“. Proccedings, Hrsg. ReliaSoft Corporation, S. 441-453.
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.

[ 5 ] Lanza, G.; Stricker, N. & Peters, S. (2013), „Ad-hoc Rescheduling and Innovative Business Models for Shock-robust Production Systems“. Procedia CIRP Volume 7, Hrsg. Pedro F. Cunha, S. 121-126.
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).

[ 6 ] Lanza, G.; Stoll, J.; Stricker, N.; Peters, S. & Lorenz, C. (2013), „Measuring Global Production Effectiveness“. Procedia CIRP Volume 7, Hrsg. Cunha, P. F., Elsevier, S. 31-36.
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.

[ 7 ] Lanza, G.; Appel, D. & Stricker, N. (2013), „TCO 2.0 - Ein Weg zu mehr Transparenz und Kommunikation“, wt Werkstattstechnik online, S. 605-609.
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.

[ 8 ] Lanza, G.; Ruhrmann, S.; Stricker, N. & Kohl, M. (2013), „Optimization Model for value-added networks of globally operating companies “. Proceedings of 22nd International Conference on Production Research, Hrsg. International Foundation for Production Research, S. 1-7.
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.

[ 9 ] Lanza, G.; Stricker, N. & Stoll, J. (2013), „Innovative product-services for robust global supply chains - a viewpoint“. Proceedings of the 17th Cambridge International Manufacturing Symposium, Hrsg. University of Cambrigde, S. 386-400.
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.

[ 10 ] Lanza, G.; Stricker, N. & Moser, R. (2013), „Concept of an intelligent Production Control for Global Manufacturing in dynamic Environments based on Rescheduling“. Proceedings of the 2013 IEEE, Hrsg. IEEE, S. 315-319.
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.

[ 11 ] Appel, D.; Genssler, K.; Stricker, N. & Lanza, G. (2014), „Interdisciplinarity as a success factor—service and reliability planning integrated in a production model“. Safety, Reliability and Risk Analysis Beyond the Horizon, Hrsg. Steenbergen et al. (Eds), S. 1325-1332.
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.

[ 12 ] Stricker, N.; Loeper, O. & Lanza, G. (2014), „Bewertungskriterien von Rescheduling-Produktionsplänen“, wt Werkstattstechnik online, S. 230-233.
"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.

[ 13 ] Stricker, N.; Kopf, R. & Lanza, G. (2014), „Solving multi-criteria problems under risk: an approach explained using the example of rescheduling in dynamic environments“, Production Engineering, Nr. 4, S. 535-541.
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.

[ 14 ] Dosch, S.; Häfner, B.; Kopf, R.; Sell-Le Blanc, F. & Stricker, N. (2014), „Life Cycle Performance von Produktionssystemen - Eine ganzheitliche Betrachtung der Produktion auf allen Ebenen mithilfe der OEE“, wt Werkstattstechnik online, Band 7, S. 481-484.
Die Betrachtung der Life Cycle Performance von Produktionssystemen verlangt eine ganzheitliche Sicht auf das System mit allen darin installierten Anlagen, Komponenten und Prozessen in verschiedensten Teilbereichen. Neben der reinen Betrachtung der Produktionsleistung sind auch die Bereiche Qualitäts- und Instandhaltungsmanagement zu berücksichtigen. Hierbei findet häufig die OEE (Overall Equipment Effectiveness)-Kennzahl Anwendung.

[ 15 ] Stricker, N. & Lanza, G. (2014), „An Approach towards improving the Robustness of ProductionSystems“. Tagungsband zum wgp Kongress, Hrsg. Trans Tech Publications, S. 461-468.
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.

[ 16 ] Stricker, N. & Lanza, G. (2014), „The concept of robustness in production systems and its correlation to Disturbances“. Procedia CIRP 19, Hrsg. Elsevier, S. 461-468.
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.

[ 17 ] Stricker, N. (2014), „Stabilisierung des Leistungsgrads durch robuste Produktionssysteme“. Life-Cycle-Performance von Produktionssystemen, Hrsg. Jürgen Fleischer, V. S., Shaker Verlag, S. 42-57.
Robuste Produktionssysteme zeichnen sich durch eine stabile und hohe Performance aus. Am Beispiel einer Montagelinie wird im Beitrag aufgezeigt, wie die Robustheit des Leistungsgrades verbessert werden kann. Basierend auf einer Störungsanalyse- und Klassifikation werden zunächst die relevantesten Störungsursachen identifiziert, bevor auf potentielle Verbesserungsmaßnahemn eingagangen wird. Die Maßnahem werden evaluiert.

[ 18 ] Lanza, G.; Peters, S.; Arndt, T.; Häfner, B. & Stricker, N. (2014), „Die Produktion im Jahr 2025 - ein Zukunftsbild“, Industrie Management, Nr. 6, S. 64-66.
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".

[ 19 ] Stricker, N. .; Pfeiffer, A.; Moser, E.; Kádár, B.; Lanza, G. & Monostori, L. . (2015), „Supporting multi-level and robust production planning and execution“, Operating current production systems influenced by the factors of increasing dynamics and volatility poses a need for robustness. Among different enablers for robustness the appropriate ones for specific production systems have to be identified and evalua, S. 415-418.
Operating current production systems influenced by the factors of increasing dynamics and volatility poses a need for robustness. Among different enablers for robustness the appropriate ones for specific production systems have to be identified and evaluated. In this cooperative paper multi-objective decision support models will be presented evaluating the best enablers for the levels of production network, plant and shop-floor. The suggested models for the stabilization of the production system's performance under volatile environment use analytical and simulation based approaches on the regarded levels.

[ 20 ] Moser, E.; Stricker, N.; Liebrecht, C.; Hiller, A.; Ziegler, M. & Lanza, G. (2016), „Migration Planning for Global Production Networks using Markovian Decision Processes“. IFAC-PapersOnLine, Hrsg. International Federation of Automatic Control, S. 35-40.
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.

[ 21 ] Stricker, N.; Moser, E. & Lanza, G. (2016), „The concept of Robustness in Production Systems“. Enterprise Interoperability in the Digitized and Networked Factory of the Future, Hrsg. I-ESA, S. 395-401.
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.

[ 22 ] Becker, J.; Kadar, B.; Colledani, M.; Stricker, N.; Urgo, M.; Unglert, J.; Gyulai, D. & Moser, E. (2016), „The RobustPlaNet Project: Towards Shock-Robust Design Of Plants And Their Supply Chain Networks“. IFAC-PapersOnLine, Hrsg. International Federation of Automatic Control, S. 29-34.
This paper provides an overview of the research goals and current research status of the EU-FP7 project RobustPlaNet. A description of the general concept and vision of the project is presented and the adopted definition of robustness at plant and supply chain levels are discussed. Moreover, the RobustPlaNet approach and its innovative technologies and methods are described, followed by a summary of the different industrial use cases. The architecture of the decision support cockpit that will emerge from the integration of these tools is presented. At last, the overall impact of the RobustPlaNet solution is discussed, supporting the European manufacturing industry in the transition towards shock-robust plants and supply chains

[ 23 ] Stricker, N.; Pfeiffer, A.; Moser, E.; Kádár, B. & Lanza, G. (2016), „Performance measurement in flow lines – Key to performance improvement“, CIRP Annals - Manufacturing Technology, S. 463-466.
Key Performance Indicators (KPIs) are frequently used for measuring a production systems’ performance. The selection of KPIs should lead to a set being as small as possible but taking into account all relevant aspects of the system. This paper provides an analytical approach to determine the set of relevant KPIs for specific production lines, allowing for a transparent and complete performance measurement. An LP was formulated for the proposed KPI model and a significant reduction of the number of KPIs used could be realized. The analytical model was tested in a real industrial application.

[ 24 ] Greinacher, S.; Echsler Minguillon, F.; Häfner, B.; Stricker, N. & Lanza, G. (2016), „Skalierbare Automatisierung und Industrie 4.0“, wt Werkstattstechnik online, Nr. 9, S. 659-665.
Industrie 4.0 ist ein Enabler für wandlungsfähige Montagesysteme. Am Beispiel der skalierbaren Automatisierung eines Montagesystems für Elektromotoren wird der effektive Einsatz von Industrie 4.0-Konzepten und -Komponenten aufgezeigt. Exemplarisch werden die Applikation einer dezentralen Steuerung sowie ein integriertes Robotiksystem vorgestellt. Erst die Kombination der Industrie 4.0-Elemente erlaubt ein plug&produce-fähiges Montagesystem, das auf veränderte Anforderungen reagieren kann.

[ 25 ] Stricker, N.; Micali, M.; Dornfeld, D. & Lanza, G. (2016), „Considering Interdependencies of KPIs“. Procedia Manufacturing, Hrsg. Elsevier, S. 300-307.
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.

[ 26 ] Stricker, N.; Echsler Minguillon, F. & Lanza, G. (2017), „Selecting key performance indicators for production with a linear programming approach“, International Journal of Production Research, S. 5537-5549. https://doi.org/10.1080/00207543.2017.1287444
Modern production systems are prone to disruptions due to shorter product life cycles, growing variant diversity and progressively distributed production. At the same time, reduced time and capacity buffers diminish mitigation opportunities, requiring better tools for production control. Performance measurement with key performance indicators (KPIs) is a widely used instrument to detect changes in production system performance in order to coordinate appropriate countermeasures. The main challenge in planning KPI systems consists in determining relevant KPIs. On the one hand, enough KPIs must be selected for a sufficiently high information content. On the other hand, the cognitive abilities of users are not to be overstrained by selecting too many KPIs. This tradeoff is addressed in a proposed selection process using an integer linear programme for objective KPI selection. In order to achieve this goal, crucial facets of the information content requirement are formalised mathematically. The developed method is validated using a practical application example, showing the influence of model parameter selection on optimisation results. The formalisation of the information content is shown to be a novel and promising approach.

[ 27 ] Lanza, G.; Kopf, R.; Zaiß, M.; Stricker, N.; Eschner, N.; Yang, S.; Jacob, A.; Schönle, A.; Webersinke, L. & Wirsing, L. (2017), „Laser-Strahlschmelzen - Technologie mit Zukunftspotential“. Auftraggeber: Bundesministerium für Bildung und Forschung. Ein Handlungsleitfaden, Karlsruhe, Hrsg. Wbk Institut für Produktionstechnik, ISBN/ISSN: 978-3-00-056913-5.
Additive Fertigungsverfahren haben sich in den vergangenen Jahren im Prototypenbau etabliert: Der deutlich höhere Freiheitsgrad im Bauteildesign sowie der Wegfall von Werkzeugkosten wecken das Interesse der Industrie, diese Verfahren auch für die Serienproduktion zu verwenden. Für die Fertigung mit Metallen verspricht vor allem das Laser-Strahlschmelzen (engl. Laser Beam Melting, LBM) großes Potenzial. Aus dem jetzigen Stand der Technik eignet sich dieses allerdings nur bedingt für die Serienanwendung. Um LBM an die Anforderungen und Bedürfnisse möglicher Anwender anzupassen, muss es entsprechend weiterentwickelt werden. Am wbk wurde die Studie „Laser-Strahlschmelzen – Technologie mit Zukunftspotenzial“ entwickelt, welche geeignete Maßnahmen ableitet, die das Verfahren für eine zielgerichtete Industrialisierung vorbereitet und priorisiert. Die Studie zeigt zudem zukünftige Entwicklungstrends des LBM-Verfahrens auf und kategorisiert potenzielle wirtschaftliche Einsatzgebiete der Anwender. Basierend auf 28 Interviews sowie Workshops mit anerkannten Experten aus der Industrie und Forschung ließen sich letztlich Handlungsempfehlungen für Unternehmen, Forschung, Verbände und Politik ableiten. Die notwendigen Entwicklungstätigkeiten wurden in einer Roadmap festgehalten. Deutlich wird, dass die geringe Prozessstabilität und Produktivität der LBM-Anlagen sowie der gesamten Prozesskette als größte Hürde gelten. Auch bei den verwendeten Materialien und von den entstehenden Bauteilen erwartet die Industrie große Entwicklungen. Das LBM-Verfahren eignet sich zum heutigen Zeitpunkt vor allem für Bauteile in kleinen Stückzahlen. Experten schreiben dem LBM-Verfahren ein großes Potenzial für die Serienfertigung zu. Allerdings müssen hierfür weitere Entwicklungsmaßnahmen vorgenommen werden. Die Studie definiert aus den Anforderungen der Anwender Klassen, die als besonders relevant betrachtet werden: • Variantenreiche, individualisierte Serienproduktion • Qualitätsorientierte Produktion großer Bauteile • Kostengünstige Produktion in hoher Stückzahl Diese drei Klassen stellen Extremausprägungen dar, zwischen denen sich die Anwender mehrheitlich einordnen lassen und welche die Grundlage für die Handlungsempfehlungen bilden.

[ 28 ] Stricker, N.; Kuhnle, A.; Sturm, R. & Friess, S. (2018), „Reinforcement learning for adaptive order dispatching in the semiconductor industry“, CIRP Annals - Manufacturing Technology, S. 511-514. https://doi.org/10.1016/j.cirp.2018.04.041
The digitalization of production systems tends to provide a huge amount of data from heterogeneous sources. This is particularly true for the semiconductor industry wherein real time process monitoring is inherently required to achieve a high yield of good parts. An application of data-driven algorithms in production planning to enhance operational excellence for complex semiconductor production systems is currently missing. This paper shows the successful implementation of a reinforcement learning-based adaptive control system for order dispatching in the semiconductor industry. Furthermore, a performance comparison of the learning-based control system with the traditionally used rule-based system shows remarkable results. Since a strict rulebook does not bind the learning-based control system, a flexible adaption to changes in the environment can be achieved through a combination of online and offline learning.

[ 29 ] Lanza, G.; Nyhuis, P.; Fisel, J.; Jacob, A.; Nielsen, L.; Schmidt, M. & Stricker, N. (2018), „Wandlungsfähige, menschzentrierte Strukturen in Fabriken und Netzwerken der Industrie 4.0“. Auftraggeber: Wissenschaftlicher Beirat der Plattform Industrie 4.0. Herbert Utz Verlage , München, Hrsg. Acatech.
Die menschzentrierte Wandlungsfähigkeit durch Industrie 4.0-Technologien wird in dieser Studie untersucht, wobei die Arbeitsgruppe 2 „Forschung und Innovation“ der Plattform Industrie 4.0 einbezogen wurde. Die Einbindung von Wirtschaft, Wissenschaft und Politik in Form von einem Kamingespräch, verschiedenen Experteninterviews und einem abschließenden Workshop hat nicht nur die Verdeutlichung der bisherigen Defizite, sondern auch eine Vielzahl von Analyse- und Lösungsmöglichkeiten aufgezeigt. Diese möchten wir Ihnen hier präsentieren.

[ 30 ] Lorenz, R.; Lorentzen, K.; Stricker, N. & Lanza, G. (2018), „Applying User Stories for a customer-driven Industry 4.0 Transformation“. Proceedings of 16th IFAC Symposium on Information Control Problems in Manufacturing, Hrsg. IFAC .
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.