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Design and simulation of assembly line feeding systems in the automotive sector using supermarket, kanbans and tow trains: a general framework

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  • Maurizio Faccio
  • Mauro Gamberi
  • Alessandro Persona
  • Alberto Regattieri
  • Fabio Sgarbossa

Abstract

A growing number of manufacturers are adopting the so-called supermarket strategy to supply components to the production system. Supermarkets are decentralized storage areas used as intermediate warehouses for parts required by the production system (typically assembly lines). Such a feeding system is widely used in the automotive industry where assembly stations in multiple mixed-model assembly lines are usually refilled by means of a systematic part replenishment driven by Kanban systems, adopting small trucking vehicles towing some wagons (tow trains). The aim of this paper is to provide a simple but robust framework in order to design the supermarket/feeding system dedicated to complex multiple mixed-model assembly lines. This framework proposes an integrated approach both for long-term (static analytical model) and short-term (dynamic simulation) problems dealing with Kanban and Supermarket systems dedicated to assembly lines, and the tow train fleet sizing and management. This proposed methodology is applied to a case study derived from the Italian automotive industry, and the results highlight the high interrelation between the long and the short term variables that can be evaluated only by an integrated approach that considers both static and dynamic aspects of the problem. The results of this study are then presented and widely discussed. Copyright Springer-Verlag Berlin Heidelberg 2013

Suggested Citation

  • Maurizio Faccio & Mauro Gamberi & Alessandro Persona & Alberto Regattieri & Fabio Sgarbossa, 2013. "Design and simulation of assembly line feeding systems in the automotive sector using supermarket, kanbans and tow trains: a general framework," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 24(2), pages 187-208, July.
    • Handle: RePEc:spr:metrik:v:24:y:2013:i:2:p:187-208
    DOI: 10.1007/s00187-013-0175-1
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    References listed on IDEAS

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    Cited by:

    1. Masood Fathi & Morteza Ghobakhloo, 2020. "Enabling Mass Customization and Manufacturing Sustainability in Industry 4.0 Context: A Novel Heuristic Algorithm for in-Plant Material Supply Optimization," Sustainability, MDPI, vol. 12(16), pages 1-15, August.
    2. Francesco Lolli & Rita Gamberini & Claudio Giberti & Bianca Rimini & Federica Bondi, 2016. "A simulative approach for evaluating alternative feeding scenarios in a kanban system," International Journal of Production Research, Taylor & Francis Journals, vol. 54(14), pages 4228-4239, July.
    3. Boysen, Nils & Emde, Simon & Hoeck, Michael & Kauderer, Markus, 2015. "Part logistics in the automotive industry: Decision problems, literature review and research agenda," European Journal of Operational Research, Elsevier, vol. 242(1), pages 107-120.
    4. Simon Emde & Michael Schneider, 2018. "Just-In-Time Vehicle Routing for In-House Part Feeding to Assembly Lines," Transportation Science, INFORMS, vol. 52(3), pages 657-672, June.
    5. C. Briand & Y. He & S. U. Ngueveu, 2018. "Energy-efficient planning for supplying assembly lines with vehicles," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(4), pages 387-414, December.

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