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Automotive supply chain logistics: container demand planning using Monte Carlo simulation

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  • Florian Klug

Abstract

Car manufacturers are continuously examining ways to reduce logistics costs combined with higher performance in inbound delivery. The increasingly important role of packaging in the efficient and effective operation of multi-site car manufacturing needs to develop a planning model of container demand that better fulfils the prerequisites posed by dynamic supply chains in automotive industry. The paper analyses critical issues in container demand planning of the product development phase of a new car model before start of production. A quantitative methodology with Monte Carlo simulations is used to incorporate the uncertainty of valuation parameters. The research is based on real case study data of European auto industry in a multi-tier inbound transport network. The proposed methodology contributes to the current demand for computational support for logistics planning. In addition, it may reveal potential weakness in standard approaches for container demand planning.

Suggested Citation

  • Florian Klug, 2011. "Automotive supply chain logistics: container demand planning using Monte Carlo simulation," International Journal of Automotive Technology and Management, Inderscience Enterprises Ltd, vol. 11(3), pages 254-268.
    • Handle: RePEc:ids:ijatma:v:11:y:2011:i:3:p:254-268
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    Cited by:

    1. Volker Trauzettel, 2015. "A Case Study On Optimizing Parts Supply In Manufacturing By Reusable Containers," Business Logistics in Modern Management, Josip Juraj Strossmayer University of Osijek, Faculty of Economics, Croatia, vol. 15, pages 161-174.

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