Mid-Term Model-Plant Allocation for Flexible Production Networks in the Automotive Industry

  • Kai Wittek
  • Achim Koberstein
  • Thomas S. Spengler
Conference paper
Part of the Operations Research Proceedings book series (ORP)

Abstract

In order to match capacity with volatile demand, original equipment manufacturers in the automotive industry increase plant flexibility. This allows for car models to be re-allocated between plants over time, to optimally use available capacity. The planning problem moves from the strategic to the tactical level. Decision support in the form of mathematical planning models accounting for the increased flexibility and characteristics of the mid-term planning situation is required. Two different modeling approaches are considered in this work and compared for their applicability to the planning situation: An approach based on a single time index model formulation and an approach based on a double time index formulation. They differ in their computational time and ability to integrate lost customer rates.

Keywords

Automotive Industry Mixed Integer Linear Programming Time Index Mixed Integer Linear Programming Model Freight Transportation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Bihlmaier, R., Koberstein, A., Obst, R.: Modeling and optimizing of strategic and tactical production planning in the automotive industry. OR Spectrum 31, 311–336 (2009)CrossRefGoogle Scholar
  2. 2.
    Fleischmann, B., Ferber, S.; Henrich, P.: Strategic planning of BMW’s global production network. Interfaces 36, 194–208 (2006)CrossRefGoogle Scholar
  3. 3.
    Francas, D., Kremer, M., Minner, S., Friese, M.: Strategic process flexibility under lifecycle demand. Int. J. Prod. Econ. 121, 427–440 (2009)CrossRefGoogle Scholar
  4. 4.
    Jordan, W.C., Graves, S.C.: Principles on the benefits of manufacturing process flexibility. Manage. Sci. 41, 577–594 (1995)CrossRefGoogle Scholar
  5. 5.
    Kauder, S., Meyr, H.: Strategic network planning for an international automotive manufacturer. OR Spectrum 31, 507–532 (2009)CrossRefGoogle Scholar
  6. 6.
    Mairs, T.G., Wakefield, G.W., Johnson, E.L., Spielberg, K.: On a production allocation and distribution problem. Manage. Sci. 24, 1622–1630 (1978)CrossRefGoogle Scholar
  7. 7.
    Meyr, H.: Supply chain planning in the German automotive industry. OR Spectrum 26, 447–470 (2004)CrossRefGoogle Scholar
  8. 8.
    Pochet, Y.,Wolsey, L.A.: Production planning by mixed integer programming. Springer, New York (2006)Google Scholar
  9. 9.
    Powell, W.B., Bouza¨ıene-Ayari, B., Simao, H.P.: Dynamic models for freight transportation. In: Barnhart, C., Laporte, G. (eds.) Handbook in OR & MS, Vol. 14, pp. 285-365. Elsevier, Amsterdam (2007)Google Scholar
  10. 10.
    Sethi, A.K., Sethi, S.P.: Flexibility in manufacturing: A survey. Int. J. Flex. Manuf. Sys. 2, 289–328 (1990)CrossRefGoogle Scholar
  11. 11.
    Stephan, H.A., Gschwind, T., Minner, S.: Manufacturing capacity planning and the value of multi-stage stochastic programming under Markovian demand. Flex. Serv. Manuf. J. 22, 143–162 (2010)CrossRefGoogle Scholar
  12. 12.
    Timpe, C.H., Kallrath, J.: Optimal planning in large multi-site production networks. Eur. J. Opr. Res. 126, 422–435 (2000)CrossRefGoogle Scholar
  13. 13.
    Walter, M., Sommer-Dittrich, T., Zimmermann, J.: Evaluating volume flexibility instruments by design-of-experiments methods. Int. J. Prod. Res. 49, 1731–1752 (2011)CrossRefGoogle Scholar
  14. 14.
    Wittek, K., Volling, T., Spengler, T.S., Gundlach, F.-W.: Tactical planning in flexible production networks in the automotive industry. In: Hu, B., Morasch, K., Pickl, S., Siegle, M.(eds.) Operations Research Proceedings 2010, pp. 429-434. Springer, Berlin (2011)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Kai Wittek
    • 1
  • Achim Koberstein
    • 2
  • Thomas S. Spengler
    • 1
  1. 1.Institute of Automotive Management and Industrial ProductionTechnische Universität BraunschweigBraunschweigGermany
  2. 2.Decision Support & Operations Research LabUniversität PaderbornPaderbornGermany

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