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Benjamin_Haefner

Dr.-Ing. Benjamin Häfner M.Sc.

Oberingenieur
Bereich: Produktionssysteme
Sprechstunden: nach Vereinbarung
Raum: 111, Geb. 50.36
Tel.: +49 721 608-42444
Fax: +49 721 608-45005
Benjamin HaefnerBus7∂kit edu

Campus Süd



Dipl.-Wi.-Ing. Benjamin Häfner M.Sc.

Forschungs- und Arbeitsgebiete:

  • Mikromesstechnik
  • Qualitätsabhängige Lebensdauerprognose von Mikrozahnrädern

Allgemeine Aufgaben:

  • Vorlesungsbetreuer Quality Management
  • Lernfabrik

Projekte:

Veröffentlichungen

[ 1 ] Lanza, G.; Schulze, V.; Stockey, S.; Chlipala, M. & Haefner, B. (2012), „Automated Measurement Data Analysis for Micro Structured Surfaces“. Proceedings of 12th International Conference of the European Society for Precision Engineering & Nanotechnology, Hrsg. European Society for Precision Engineering & Nanotechnology, Sieca Repro, S. 235-238.
Abstract:
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.

[ 2 ] Lanza, G.; Viering, B. & Haefner, B. (2012), „Experimental Approach for Proposing the Lifetime of Micro Gears Through Their Shape Deviations“. Proceedings of CIRP General Assembly, Hrsg. Springer, S. 1-12.
Abstract:
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.

[ 3 ] Lanza, G.; Blank, T. & Haefner, B. (2013), „Design for Testability for Micro-Mechatronic Systems“. Proceedings of 23rd CIRP Design Conference, Hrsg. Elsevier, Springer-Verlag, S. 283-292.
Abstract:
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.

[ 4 ] Haefner, B. & Lanza, G. (2015), „Funktionsorientierte Qualitätssicherung zur Lebensdauerprognose von Mikrozahnrädern“. Tagungsband zum 5. Kongress zur Getriebeproduktion (GETPRO), Hrsg. Forschungsvereinigung Antriebstechnik e.V., S. 267-278.
Abstract:
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.

[ 5 ] Haefner, B. & Lanza, G. (2015), „Function-Oriented Measurements of Micro Gears for Lifetime Evaluation“. Proceedings of SENSOR 2015, S. 441-446.
Abstract:
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.

[ 6 ] Haefner, B.; Quiring, M.; Gullasch, J.; Glaser, G. & Lanza, G. (2015), „Finite Element Simulation for Quality Dependent Lifetime Analysis of Micro Gears“. Procedia CIRP, Hrsg. Elsevier, S. 41-46.
Abstract:
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.

[ 7 ] Lanza, G.; Haefner, B. & Krämer, A. (2015), „Optimization of selective assembly and adaptive manufacturing by means of cyber-physical system based matching“, CIRP Annals - Manufacturing Technology, S. 399-402.
Abstract:
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.

[ 8 ] Lanza, G.; Moser, E.; Stoll, J. & Haefner, B. (2015), „Learning Factory on Global Production“. Procedia CIRP, Hrsg. Kreimeier, D., Elsevier, S. 120-125.
Abstract:
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.

[ 9 ] Haefner, B. & Lanza, G. (2015), „Quality Dependent Lifetime Prognosis of Micro Gears“. Proceedings International Conference on Gears 2015, Hrsg. VDI, S. 1-10.
Abstract:
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