Strategic Manufacturing Network Performance Assessment Tool
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Gwen Louis Steier
Gwen Louis Steier, M. Sc., studied industrial engineering with a major in mechanical engineering at TU Darmstadt and the Karlsruhe Institute of Technology (KIT). Since 2020, he has been working as a research associate at the wbk Institute of Production Science at KIT in the Production Systems department and investigating global production strategies.
,
Kevin Gleich
Kevin Gleich, M. Sc., studied industrial engineering at the Karlsruhe Institute of Technology (KIT). He is a research associate at the wbk Institute of Production Science of KIT in the department of Production Systems with a focus on manufacturing network configuration.
Prof. Dr.-Ing. Gisela Lanza studied industrial engineering at the Karlsruhe Institute of Technology (KIT) and held the first shared professorship “Global Production Engineering and Quality” at KIT in cooperation with Daimler AG. Since 2003, she has been head of the Production Systems Department at the wbk Institute of Production Science of KIT.
Abstract
The long-term configuration of the production network includes the allocation of products and processes. Numerous, sometimes conflicting objectives are pursued, such as market access, economies of scale and risk mitigation. However, in order to systematically configure the network, it is necessary to strategically analyse the strengths and weaknesses of the sites. This article presents a fuzzy inference-based approach for the holistic evaluation of the production networks. The tool was applied in two practical case studies. The results and implications are also presented.
Abstract
Die langfristige Konfiguration des Produktionsnetzes ist ein hochkomplexes Entscheidungsfeld. Die Allokation von Produkten, Prozessen und Ressourcen ist das Ergebnis zahlreicher, sich gegenseitig überlagernder strategischer Motive wie Marktzugang, Skalenerträge und Risikominderung. Der Ausgangspunkt für die Netzwerkkonfiguration ist die Analyse des bestehenden Produktionsnetzwerks. In diesem Beitrag wird ein Fuzzy-Inferenz-basierter Ansatz zur ganzheitlichen Bewertung von Produktionsnetzwerken vorgestellt. Das Instrument wurde in zwei praktischen Fallstudien angewandt. Die Ergebnisse und Implikationen werden ebenfalls vorgestellt.
Note
This article is peer reviewed by the members of the ZWF Advisory Board.
About the authors
Gwen Louis Steier, M. Sc., studied industrial engineering with a major in mechanical engineering at TU Darmstadt and the Karlsruhe Institute of Technology (KIT). Since 2020, he has been working as a research associate at the wbk Institute of Production Science at KIT in the Production Systems department and investigating global production strategies.
Kevin Gleich, M. Sc., studied industrial engineering at the Karlsruhe Institute of Technology (KIT). He is a research associate at the wbk Institute of Production Science of KIT in the department of Production Systems with a focus on manufacturing network configuration.
Prof. Dr.-Ing. Gisela Lanza studied industrial engineering at the Karlsruhe Institute of Technology (KIT) and held the first shared professorship “Global Production Engineering and Quality” at KIT in cooperation with Daimler AG. Since 2003, she has been head of the Production Systems Department at the wbk Institute of Production Science of KIT.
Acknowledgements
We extend our sincere gratitude to the Deutsche Forschungsgesellschaft (DFG, German Research Foundation) for supporting this research project “Level of Decentralisation of Global Production Networks – Strategy-oriented Design of Decision-making Autonomy” (513193218).
Literature
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© 2024 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
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- Editorial
- Strategien der Produktion
- Global Production
- Managing Global Manufacturing 2025+
- Current Topics in International Manufacturing
- Strategic Manufacturing Network Performance Assessment Tool
- Tactical Order Allocation in International Manufacturing Networks
- Centralism or Autonomy?
- Company-Specific Plant Roles
- Network Capability Configurations as a Catalyst for Competitive Advantage
- Integrating Risk into the Analysis
- Interview
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- Tribologie
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- Energieeffizienz
- Vom Verbrauchsmonitoring zur Verbrauchsprognose
- Künstliche Intelligenz
- Integration eines ChatGPT-gestützten Part Vectorizers in das Trichter-Sieb-Modell
- Digitale Zwillinge
- Simulationsgestützte Optimierung globaler Produktionsnetzwerke
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Articles in the same Issue
- Frontmatter
- Editorial
- Strategien der Produktion
- Global Production
- Managing Global Manufacturing 2025+
- Current Topics in International Manufacturing
- Strategic Manufacturing Network Performance Assessment Tool
- Tactical Order Allocation in International Manufacturing Networks
- Centralism or Autonomy?
- Company-Specific Plant Roles
- Network Capability Configurations as a Catalyst for Competitive Advantage
- Integrating Risk into the Analysis
- Interview
- Wir denken unsere Prozesse neu!
- Nachhaltigkeit
- Nachhaltige Produktionsoptimierung
- Substitution von energieintensiven Primärmaterialien
- Geschäftsmodelle
- Geschäftsmodellentwicklung für Kreislaufwirtschaft und Nachhaltigkeit
- Fehlerprävention
- Prädiktion menschlicher Fehler in der Linienmontage
- Tribologie
- Ressourceneffiziente Prozesse durch modifizierte Werkzeugoberflächen
- Energieeffizienz
- Vom Verbrauchsmonitoring zur Verbrauchsprognose
- Künstliche Intelligenz
- Integration eines ChatGPT-gestützten Part Vectorizers in das Trichter-Sieb-Modell
- Digitale Zwillinge
- Simulationsgestützte Optimierung globaler Produktionsnetzwerke
- Digitalisierung
- Business Engineering
- Die Konvergenz des Building Information Models und des Digitalen Zwillings im Fabriklebenszyklus
- Vorschau
- Vorschau
