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An optimal structured policy for maintenance of partially observable aircraft engine components

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  • Wallace J. Hopp
  • Yar‐Lin Kuo

Abstract

This paper considers the maintenance of aircraft engine components that are subject to stress. We model the deterioration process by means of the cumulative jump process representation of crack growth. However, because in many cases cracks are not easily observable, maintenance decisions must be made on the basis of other information. We incorporate stress information collected via sensors into the scheduling decision process by means of a partially observable Markov decision process model. Using this model, we demonstrate the optimality of structured maintenance policies, which support practical maintenance schedules. © 1998 John Wiley & Sons, Inc. Naval Research Logistics 45: 335–352, 1998

Suggested Citation

  • Wallace J. Hopp & Yar‐Lin Kuo, 1998. "An optimal structured policy for maintenance of partially observable aircraft engine components," Naval Research Logistics (NRL), John Wiley & Sons, vol. 45(4), pages 335-352, June.
    • Handle: RePEc:wly:navres:v:45:y:1998:i:4:p:335-352
    DOI: 10.1002/(SICI)1520-6750(199806)45:43.0.CO;2-6
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    References listed on IDEAS

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    1. Wallace J. Hopp & Sung‐Chi Wu, 1988. "Multiaction maintenance under markovian deterioration and incomplete state information," Naval Research Logistics (NRL), John Wiley & Sons, vol. 35(5), pages 447-462, October.
    2. Donald Rosenfield, 1976. "Markovian Deterioration with Uncertain Information," Operations Research, INFORMS, vol. 24(1), pages 141-155, February.
    3. Donald Rosenfield, 1976. "Markovian Deterioration With Uncertain Information — A More General Model," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 23(3), pages 389-405, September.
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    Cited by:

    1. Yarlin Kuo & Zi‐Ann Chang, 2007. "Integrated production scheduling and preventive maintenance planning for a single machine under a cumulative damage failure process," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(6), pages 602-614, September.
    2. Daming Lin & Viliam Makis, 2006. "On‐line parameter estimation for a partially observable system subject to random failure," Naval Research Logistics (NRL), John Wiley & Sons, vol. 53(5), pages 477-483, August.
    3. Michele Compare & Paolo Marelli & Piero Baraldi & Enrico Zio, 2018. "A Markov decision process framework for optimal operation of monitored multi-state systems," Journal of Risk and Reliability, , vol. 232(6), pages 677-689, December.

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