wbk Institute of Production Science

Martin Benfer, M.Sc.

  • 76131 Karlsruhe
    Kaiserstraße 12

Benfer Martin, M.Sc.

Area of Research:

  • Global Production Strategies
  • Digital Twin of Global Production Networks
  • Production network modeling and simulation
  • Traceability in global value creation
  • Transparency in the value chain

 

General Tasks:

  • Coordination of Lecture Global Production
  • Coordination of Lecture Hector Global Production
  • Lernfabrik „Global Production“ (http://globallearningfactory.com/) – Lean and Industry 4.0

 

Projects:

  • AiF TransNet – Transparency in global production networks
  • BaWü PoTracE – Traceability platform for the remanufacturing of e-mobility solutions

 

Curriculum Vitae:

since 11/2019

Research Associate at the Institute of Production Science (wbk) at Karlsruhe Institute of Technology (KIT)

10/2017 – 09/2019

Master Development and Design Engineering at RWTH Aachen University and research exchange with the University of Southern California, LA

10/2013 – 10/2017 

Bachelor Mechanical Engineering at the RWTH Aachen University

Publications

[ 1 ] Benfer, M.; Ziegler, M.; Gützlaff, A.; Franken, B.; Cremer, S.; Prote, J. & Schuh, G. (2019), "Determination of the abstraction level in production network models". Procedia CIRP, eds. Elsevier, pp. 198-203.
Abstract
In recent years the importance of production network modeling has increased significantly, as companies face rising complexity and dynamics in their environment. Quantitative models help to gain understanding and support strategic decision making in production network management. Choosing the right abstraction level by determining the trade-off between model accuracy and effort for modeling is crucial for developing viable and applicable models. While experienced model builders can identify the right abstraction level intuitionally, a structured process would lead to results which are more consistent. This paper presents an approach to structure and streamline the determination of the abstraction level. A basic concept is presented, that enables systematic definition of the abstraction level for a given model framework. A process implementing the concept is proposed, that helps to identify the right abstraction level based on case-specific requirements and restrictions and tailor the model to solve the examined problem. The process is tested in a case study at a globally operating tooling machine company.

[ 2 ] Benfer, M.; Gartner, P.; Treber, S.; Kuhnle, A.; Häfner, B. & Lanza, G. (2020), "Implementierung von unternehmensübergreifender Traceability", ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, vol. 5, pp. 304-308. 10.3139/104.112284 [19.06.20].
Abstract
Die Nachverfolgbarkeit (engl. traceability) von Produkten entlang ihres Lebenszyklus ist eine Grundvoraussetzung für zahlreiche Anwendungsfelder: der Ermöglichung von Kreislaufwirtschaftsprozessen, dem Schutz vor Produktpiraterie und der zielgerichteten Qualitätssicherung. Jedoch existieren über die gesetzlich vorgeschriebenen Standards hinaus wenig umfassende Lösungen, um Produkte unternehmensübergreifend nachzuverfolgen. Dieser Beitrag zeigt ein Konzept zur strukturierten Konzeption, Implementierung und Bewertung solcher Traceability-Systeme.

[ 3 ] Treber, S.; Benfer, M.; Häfner, B.; Wang, L. & Lanza, G. (2021), "Robust optimization of information flows in global production networks using multi-method simulation and surrogate modelling", CIRP Jorunal of Manufacturing Science and Technology, vol. 32, pp. 491-506. 10.1016/j.cirpj.2020.08.012 [20.03.04].
Abstract
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.