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Maintenance and flight scheduling of low observable aircraft

Author

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  • Philip Cho
  • Vivek Farias
  • John Kessler
  • Retsef Levi
  • Thomas Magnanti
  • Eric Zarybnisky

Abstract

In this article, we focus on relatively new maintenance and operational scheduling challenges that are faced by the United States Air Force concerning low‐observable (LO) or stealth aircraft. The LO capabilities of an aircraft degrade stochastically as it flies, making it difficult to make maintenance scheduling decisions. Maintainers can address these damages, but must decide, which aircraft should be put into maintenance, and for how long. Using data obtained from an active duty Air Force F‐22 wing and interviews with Air Force maintainers and program specialists, we model this problem as a generalization of the well‐known restless multiarmed bandit superprocess. Specifically, we use an extension of the traditional model to allow for actions that require varying lengths of time, and generate two separate index policies from a single model; one for maintenance actions and one for the flying action. These index policies allow maintenance schedulers to intuitively, quickly, and effectively rank a fleet of aircraft based on each aircraft's LO status and decide, which aircraft should enter into LO maintenance and for how long, and which aircraft should be used to satisfy daily sortie requirements. Finally, we present extensive data‐driven, detailed simulation results, where we compare the performance of the index policies against policies currently used by the Air Force, as well as some other possible more naive heuristics. The results indicate that the index policies significantly outperform existing policies in terms of fully mission capable (FMC) rates. In particular, the experiments highlight the importance of coordinated maintenance and flying decisions. © 2015 Wiley Periodicals, Inc. 62:60–80, 2015

Suggested Citation

  • Philip Cho & Vivek Farias & John Kessler & Retsef Levi & Thomas Magnanti & Eric Zarybnisky, 2015. "Maintenance and flight scheduling of low observable aircraft," Naval Research Logistics (NRL), John Wiley & Sons, vol. 62(1), pages 60-80, February.
    • Handle: RePEc:wly:navres:v:62:y:2015:i:1:p:60-80
    DOI: 10.1002/nav.21614
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    References listed on IDEAS

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    1. Glazebrook, K. D. & Mitchell, H. M. & Ansell, P. S., 2005. "Index policies for the maintenance of a collection of machines by a set of repairmen," European Journal of Operational Research, Elsevier, vol. 165(1), pages 267-284, August.
    2. Christos H. Papadimitriou & John N. Tsitsiklis, 1999. "The Complexity of Optimal Queuing Network Control," Mathematics of Operations Research, INFORMS, vol. 24(2), pages 293-305, May.
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    Cited by:

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    2. Abderrahmane Abbou & Viliam Makis, 2019. "Group Maintenance: A Restless Bandits Approach," INFORMS Journal on Computing, INFORMS, vol. 31(4), pages 719-731, October.

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