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“ ( – Agile Production Networks



  • 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


[ 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. 10.1016/j.procir.2019.03.035
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
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
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.

[ 4 ] Benfer, M.; Peukert, S. & Lanza, G. (2021), "Operations Research in International Manufacturing Networks" in Global Manufacturing Management, eds. Friedli, T.; Lanza, G. & Remling, D., Springer, Cham, pp. 219-231. ISBN/ISSN: 978-3-030-72740-6
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.

[ 5 ] Gartner, P.; Benfer, M.; Kuhnle, A. & Lanza, G. (2021), "Potentials of Traceability Systems - a Cross-Industry Perspective". Elsevier, 10.1016/j.procir.2021.11.166
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.

[ 6 ] Benfer, M.; Peukert, S. & Lanza, G. (2021), "A Framework for Digital Twins for Production Network Management". Procedia CIRP, Elsevier, pp. 1269-1274. 10.1016/j.procir.2021.11.213
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.

[ 7 ] Benfer, M.; Verhaelen, B.; Peukert, S. & Lanza, G. (2021), "Resilience Measures in Global Production Networks: A Literature Review and Conceptual Framework", Die Unternehmung, vol. 75, no. 4, 10.5771/0042-059X-2021-4-491
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.