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Selecting test sensitivity and specificity parameters to optimally maintain a degrading system

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  • L M Maillart
  • T G Yeung
  • Z Gozde Icten

Abstract

The formulation of a partially observed Markov decision process (POMDP) model to adaptively schedule testing, minimal repairs and overhauls for a two-state process with age-dependent degradation is presented. Structurally, the optimal maintenance policy is of control-limit type with respect to the repair and overhaul actions in both age and the probability of being out-of-control. A tailored solution algorithm is developed that iteratively determines an upper bound on the truncation age under the optimal policy. Numerical examples highlight the flexibility of the model, possible complexities of the optimal policy, and cost savings in comparison with less flexible models.

Suggested Citation

  • L M Maillart & T G Yeung & Z Gozde Icten, 2011. "Selecting test sensitivity and specificity parameters to optimally maintain a degrading system," Journal of Risk and Reliability, , vol. 225(2), pages 131-139, June.
    • Handle: RePEc:sae:risrel:v:225:y:2011:i:2:p:131-139
    DOI: 10.1177/1748007810395667
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    References listed on IDEAS

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    1. Richard D. Smallwood & Edward J. Sondik, 1973. "The Optimal Control of Partially Observable Markov Processes over a Finite Horizon," Operations Research, INFORMS, vol. 21(5), pages 1071-1088, October.
    2. William S. Lovejoy, 1987. "Some Monotonicity Results for Partially Observed Markov Decision Processes," Operations Research, INFORMS, vol. 35(5), pages 736-743, October.
    3. William S. Lovejoy, 1987. "Technical Note—On the Convexity of Policy Regions in Partially Observed Systems," Operations Research, INFORMS, vol. 35(4), pages 619-621, August.
    4. Kuo, Yarlin, 2006. "Optimal adaptive control policy for joint machine maintenance and product quality control," European Journal of Operational Research, Elsevier, vol. 171(2), pages 586-597, June.
    5. James E. Eckles, 1968. "Optimum Maintenance with Incomplete Information," Operations Research, INFORMS, vol. 16(5), pages 1058-1067, October.
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