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Monotone optimal preventive maintenance policies for stochastically failing equipment

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  • Michael Q. Anderson

Abstract

This paper examines various models for maintenance of a machine operating subject to stochastic deterioration. Three alternative models are presented for the deterioration process. For each model, in addition to the replacement decision, the option exists of performing preventive maintenance. The effect of this maintenance is to “slow” the deterioration process. With an appropriate reward structure imposed on the processes, the models are formulated as continuous time Markov decision processes. the optimality criterion being the maximization of expected discounted reward earned over an infinite time horizon. For each model conditions are presented under which the optimal maintenance policy exhibits the following monotonic structure. First, there exists a control limit rule for replacement. That is, there exists a number i* such that if the state of machine deterioration exceeds i* the optimal policy replaces the machine by a new machine. Secondly, prior to replacement the optimal level of preventive maintenance is a nonincreasing function of the state of machine deterioration. The conditions which guarantee this result have a cost/benefit interpretation.

Suggested Citation

  • Michael Q. Anderson, 1981. "Monotone optimal preventive maintenance policies for stochastically failing equipment," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 28(3), pages 347-358, September.
    • Handle: RePEc:wly:navlog:v:28:y:1981:i:3:p:347-358
    DOI: 10.1002/nav.3800280301
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    Cited by:

    1. C. Teresa Lam & R. H. Yeh, 1994. "Optimal replacement policies for multistate deteriorating systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 41(3), pages 303-315, April.
    2. 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.
    3. Nooshin Salari & Viliam Makis, 2020. "Application of Markov renewal theory and semi‐Markov decision processes in maintenance modeling and optimization of multi‐unit systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(7), pages 548-558, October.
    4. Ciriaco Valdez‐Flores & Richard M. Feldman, 1989. "A survey of preventive maintenance models for stochastically deteriorating single‐unit systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 36(4), pages 419-446, August.

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