Rainer Silbernagel, M.Sc.

  • 76131 Karlsruhe
    Kaiserstraße 12

Rainer Silbernagel, M.Sc.

Forschungs- und Arbeitsgebiete:

  • Industrie 4.0 in globalen Wertschöpfungsnetzwerken
  • Qualitätssteuerung durch Kollaboration in globalen Wertschöpfungsnetzwerk
  • Anreizsysteme und Geschäftsmodelle in kollaborierenden Wertschöpfungsnetzwerken


Allgemeine Aufgaben:

  • Allgemeiner Ansprechpartner für Themen der Lehre der Gruppe Produktionssysteme (PRO)
  • Vorlesungsbetreuer der Lernfabrik globale Produktion
  • Moderator Lernfabrik globale Produktion Modul 2 – Lean und Industrie 4.0



  • ReKoNet - Datenbasierte Regelung kollaborativer Wertschöpfungsnetzwerke mittels geschützter Transparenz
  • FlexPLN - Erforschung von Modellierung und Softwaretechnologie für die flexible und integrierte Produktions- und Logistikplanung in dynamischen Netzwerken
  • SmartCoNet - Smart Control of Customer-Based Collaborative Manufacturing Networks with Secured Transparency
  • BMBF ProIQ - prozessübergreifende Qualitätsregelkreise in der Produktion von Hochpräzisionsbauteilen



seit 12/2018 Wissenschaftlicher Mitarbeiter am Institut für Produktionstechnik (wbk) des Karlsruher Instituts für Technologie (KIT)
10/2011 - 11/2018 Studium des Wirtschaftsingenieurwesens am Karlsruher Institut für Technologie (KIT)
31/08/1990 Geboren in Kirchheimbolanden



[ 1 ] Silbernagel, R.; Stamer, F.; Häfner, B.; Linzbach, J. & Lanza, G. (2019), „Kollaboration in globalen Wertschöpfungsnetzwerken“, ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, Nr. 5, S. 314-317. 10.3139/104.112085
In der heutigen Welt, geprägt von Wettbewerb zwischen globalen Wertschöpfungsnetzwerken, führen Silodenken und Protektionismus langfristig zu strategischen Wettbewerbsnachteilen. Dieser Beitrag stellt einen Ansatz vor, wie durch datenbasierte Kollaboration aller Partner eines Wertschöpfungsnetzwerkes umfassend die Potenziale der Industrie 4.0 genutzt werden können. Die Aufgabenstellung wird im Rahmen des BMBF Verbundprojekts ReKoNeT bearbeitet.

[ 2 ] Silbernagel, R.; Wagner, R.; Häfner, B. & Lanza, G. (2019), „Qualitätsregelstrategien in Wertschöpfungsnetzwerken“, wt-online, Band 109, S. 802-806.
In Zeiten der Globalisierung und Digitalisierung führen Silodenken und Protektionismus zu Wettbewerbsnachteilen aller Partner eines Wertschöpfungsnetzwerkes. Ineffizienzen zeigen sich zum Beispiel durch hohen Ausschuss und geringe Margen der Zulieferer für die Produktion hochpräziser Produkte. Der Beitrag zeigt auf, wie Kollaboration in der Supply Chain mit unternehmensübergreifenden Qualitätsregelstrategien zur Steigerung der Qualität und Senkung der Qualitätskosten beiträgt.

[ 3 ] Stamer, F.; Steinke, M.; Silbernagel, R.; Häfner, B. & Lanza, G. (2020), „Using Smart Services as a Key Enabler for Collaboration in Global Production Networks“. Elsevier, S. 730-735. 10.1016/j.procir.2020.04.065

[ 4 ] Silbernagel, R.; Gese, S.; Krupa, C. & Lanza, G. (2021), „Interfirm Collaboration in Global Production Networks“. 10.5445/IR/1000136022
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.

[ 5 ] Silbernagel, R.; Arndt, T.; Peukert, S. & Lanza Gisela, L. G. (2021), „Process Quality Improvements in Global Production Networks“ in Global Manufacturing Management, Hrsg. Friedli, T.; Lanza, G. & Remling, D., Springer, Cham, S. 167-177. ISBN/ISSN: 978-3-030-72740-6
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.

[ 6 ] Silbernagel, R.; Wagner, C.; Albers, A.; Trapp, T. & Lanza, G. (2021), „Data-Based Supply Chain Collaboration“. Procedia CIRP, Elsevier, S. 470-475. 10.1016/j.procir.2021.11.079
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.

[ 7 ] Dürr, S.; Silbernagel, R.; Bartsch, H.; Steier, G. L.; Huber, M. F. & Lanza, G. (2022), „A Data-Driven Approach for Option-Specific Order Freeze Points in Mass-Customized Production“. Andersen AL. Et al. (eds) Towards Sustainable Customization: Bridging Smart Products and Manufacturing Systems, Springer, Cham., S. 620-627. 10.1007/978-3-030-90700-6_70
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.