A Schedule Optimization Tool for Destructive and Non-Destructive Vehicle Tests

Authors

  • Jeremy Ludwig Stottler Henke Associates, Inc.
  • Annaka Kalton Stottler Henke Associates, Inc.
  • Robert Richards Stottler Henke Associates, Inc.
  • Brian Bautsch Honda R&D Americas, Inc.
  • Craig Markusic Honda R&D Americas, Inc.
  • J. Schumacher Honda R&D Americas, Inc.

DOI:

https://doi.org/10.1609/aaai.v28i2.19030

Abstract

Whenever an auto manufacturer refreshes an existing car or truck model or builds a new one, the model will undergo hundreds if not thousands of tests before the factory line and tooling is finished and vehicle production beings. These tests are generally carried out on expensive, custom-made vehicles because the new factory lines for the model do not exist yet. The work presented in this paper describes how an existing intelligent scheduling software framework was modified to include domain-specific heuristics used in the vehicle test planning process. The result of this work is a prototype scheduling tool that optimizes the overall given test schedule in order to complete the work in a given time window while minimizing the total number of vehicles required for the test schedule. Initial results are presented that show a reduction in required test vehicles compared to manual scheduling of the same tasks as well as increased capability to ask “what-if” questions to further improve the schedule.

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Published

2014-07-27

How to Cite

Ludwig, J., Kalton, A., Richards, R., Bautsch, B., Markusic, C., & Schumacher, J. (2014). A Schedule Optimization Tool for Destructive and Non-Destructive Vehicle Tests. Proceedings of the AAAI Conference on Artificial Intelligence, 28(2), 2998-3003. https://doi.org/10.1609/aaai.v28i2.19030