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  4. Volkswagen Group Logistics applies operations research to optimize supplier development
 
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Volkswagen Group Logistics applies operations research to optimize supplier development

Publikationstyp
Journal Article
Date Issued
2024-03
Sprache
English
Author(s)
Wieczorrek, Sönke  
Technische Universität Braunschweig  
Thies, Christian  orcid-logo
Resilient and Sustainable Operations and Supply Chain Management W-EXK1  
Weckenborg, Christian  
Grunewald, Martin  
Spengler, Thomas Stefan  
TORE-URI
https://hdl.handle.net/11420/42791
Journal
INFORMS journal on applied analytics  
Volume
54
Issue
2
Start Page
103
End Page
204
Citation
INFORMS Journal on Applied Analytics 54 (2): 103-204 (2024)
Publisher DOI
10.1287/inte.2022.0026
Volkswagen Group Logistics (VWGL) is responsible for the logistics and supply processes of the automotive brands of the Volkswagen Group. In this context, supplier development is vital for efficient and reliable material flows between the process partners. In recent years, VWGL implemented a collaborative approach for supplier development in logistics wherein it is crucial to identify disrupting suppliers and apply improvement measures to increase their logistics performance. Against this background, VWGL initiated a project to examine how supplier development measures can be implemented efficiently to improve the overall logistics performance of VWGL’s supply base. This paper presents the developed operations research approach, which integrates Monte Carlo simulation and a knapsack model on the specific problem of supplier development. The approach consists of three stages: (1) data preparation, (2) measure evaluation, and (3) measure allocation. The approach is validated based on 18 existing less-than-truckload networks of VWGL. We find that, on average, considerable cost savings of 31% can be achieved throughout the networks compared with VWGL’s previous procedure. A new workflow facilitates our approach to lift its potential in practical application sustainably.
Subjects
Supplier Development
Inbound logistics
Automotive
Monte Carlo Simulation
DDC Class
380: Commerce, Communications, Transport
330: Economics
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