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Ford Motor Company Implements Integrated Planning and Scheduling in a Complex Automotive Manufacturing Environment

Author

Listed:
  • Ada Y. Barlatt

    (Department of Management Sciences, University of Waterloo, Waterloo N2L 3G1, Ontario, Canada)

  • Amy Cohn

    (Industrial and Operations Engineering Department, University of Michigan, Ann Arbor, Michigan 48109)

  • Oleg Gusikhin

    (Research and Advanced Engineering, Ford Motor Company, Dearborn, Michigan 48121)

  • Yakov Fradkin

    (Research and Advanced Engineering, Ford Motor Company, Dearborn, Michigan 48121)

  • Rich Davidson

    (Information Technology, Ford Motor Company, Allen Park, Michigan 48101)

  • John Batey

    (Stamping Business Unit, Ford Motor Company, Woodhaven, Michigan 48183)

Abstract

Ford Motor Company has designed, developed, and implemented a collective system of decision support tools, supply chain visualization methods, and optimization techniques to aid its planning and scheduling in a complex automotive manufacturing environment. Although originally developed particularly for stamping plants, the system can also be applied in other manufacturing environments where setup times play a dominant role. By enabling substantial improvements in workplace planning and production scheduling, the implementation of this system has resulted in significant reductions in premium freight charges, overtime wages, and inventory costs.

Suggested Citation

  • Ada Y. Barlatt & Amy Cohn & Oleg Gusikhin & Yakov Fradkin & Rich Davidson & John Batey, 2012. "Ford Motor Company Implements Integrated Planning and Scheduling in a Complex Automotive Manufacturing Environment," Interfaces, INFORMS, vol. 42(5), pages 478-491, October.
    • Handle: RePEc:inm:orinte:v:42:y:2012:i:5:p:478-491
    DOI: 10.1287/inte.1120.0650
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    References listed on IDEAS

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    Cited by:

    1. Andreas Fink & Natalia Kliewer & Dirk Mattfeld & Lars Mönch & Franz Rothlauf & Guido Schryen & Leena Suhl & Stefan Voß, 2014. "Model-Based Decision Support in Manufacturing and Service Networks," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 6(1), pages 17-24, February.
    2. Michael Fairley & David Scheinker & Margaret L. Brandeau, 2019. "Improving the efficiency of the operating room environment with an optimization and machine learning model," Health Care Management Science, Springer, vol. 22(4), pages 756-767, December.

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