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Scheduling Crash Tests at Ford Motor Company

Author

Listed:
  • Daniel Reich

    (Research and Advanced Engineering, Ford Motor Company, Dearborn, Michigan 48124)

  • Yuhui Shi

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

  • Marina Epelman

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

  • Amy Cohn

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

  • Ellen Barnes

    (Product Development Safety, Ford Motor Company, Dearborn, Michigan 48124)

  • Kirk Arthurs

    (Product Development Safety, Ford Motor Company, Dearborn, Michigan 48124)

  • Erica Klampfl

    (Research and Advanced Engineering, Ford Motor Company, Dearborn, Michigan 48124)

Abstract

We consider the problem of scheduling crash tests for new vehicle programs at Ford. We describe the development of a comprehensive web-based system that automates time-consuming scheduling analyses through mathematical optimization, while also institutionalizing expert knowledge about the engineering complexities of crash testing. We present a novel integer programming model and a corresponding solution algorithm that quickly generates efficient schedules. The system’s user interface enables engineers to specify key program data and consider multiple scheduling scenarios, while using the underlying optimization model and solution algorithms as a black box.

Suggested Citation

  • Daniel Reich & Yuhui Shi & Marina Epelman & Amy Cohn & Ellen Barnes & Kirk Arthurs & Erica Klampfl, 2016. "Scheduling Crash Tests at Ford Motor Company," Interfaces, INFORMS, vol. 46(5), pages 409-423, October.
  • Handle: RePEc:inm:orinte:v:46:y:2016:i:5:p:409-423
    DOI: 10.1287/inte.2016.0855
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    References listed on IDEAS

    as
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    Cited by:

    1. Christian Weckenborg & Karsten Kieckhäfer & Thomas S. Spengler & Patricia Bernstein, 2020. "The Volkswagen Pre-Production Center Applies Operations Research to Optimize Capacity Scheduling," Interfaces, INFORMS, vol. 50(2), pages 119-136, March.
    2. Shanshan Wang & Jinlin Li & Sanjay Mehrotra, 2021. "Chance-Constrained Multiple Bin Packing Problem with an Application to Operating Room Planning," INFORMS Journal on Computing, INFORMS, vol. 33(4), pages 1661-1677, October.

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