Rainer Silbernagel, M.Sc.

  • 76131 Karlsruhe
    Kaiserstraße 12

Rainer Silbernagel, M.Sc.

Area of Research:

  • Industry 4.0 in global production networks
  • Databased collaboration in global production networks with strategies for quality control cycles
  • Incentives and business models of collaborative production networks

 

General Tasks:

  • General contact for teaching topics of the group Production Systems (PRO)
  • Lecture Coordination of Global Learning Factory
  • Workshop coach Global Learning Factory Module 2 - Lean and Industry 4.0

 

Projects:

  • ReKoNet
  • FlexPLN - Research into modeling and software technology for flexible and integrated production and logistics planning in dynamic networks
  • SmartCoNet - Smart Control of Customer-Based Collaborative Manufacturing Networks with Secured Transparency
  • BMBF ProIQ - cross-process quality control loops in the production of high-precision components

 

Curriculum Vitae:

seit 12/2018 Research Associate at the Institute of Production Science (wbk) at Karlsruhe Institute of Technology (KIT)
10/2011 - 11/2018 Study of Industrial Engineering and Management at Karlsruhe Institute of Technology (KIT)
31/08/1990 Born in Kirchheimbolanden

 

Publications

[ 1 ] Silbernagel, R.; Stamer, F.; Häfner, B.; Linzbach, J. & Lanza, G. (2019), "Kollaboration in globalen Wertschöpfungsnetzwerken", ZWF Zeitschrift für wirtschaftlichen Fabrikbetrieb, no. 5, pp. 314-317. 10.3139/104.112085
Abstract
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, vol. 109, pp. 802-806.
Abstract
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, pp. 730-735.
Abstract


[ 4 ] Silbernagel, R.; Gese, S.; Krupa, C. & Lanza, G. (2021), "Interfirm Collaboration in Global Production Networks".
Abstract
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, eds. Friedli, T.; Lanza, G. & Remling, D., Springer, Cham, pp. 167-177. ISBN/ISSN: 978-3-030-72740-6
Abstract
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.