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Nonparametric adaptive opportunity-based replacement strategies

Coolen-Schrijner, P.; Coolen, F.P.A.; Shaw, S.C.


P. Coolen-Schrijner

S.C. Shaw


We consider opportunity-based age replacement (OAR) using nonparametric predictive inference (NPI) for the time to failure of a future unit. Based on n observed failure times, NPI provides lower and upper bounds for the survival function for the time to failure Xn+1 of a future unit which lead to upper and lower cost functions, respectively, for OAR based on the renewal reward theorem. Optimal OAR strategies for unit n+1 follow by minimizing these cost functions. Following this strategy, unit n+1 is correctively replaced upon failure, or preventively replaced upon the first opportunity after the optimal OAR threshold. We study the effect of this replacement information for unit n+1 on the optimal OAR strategy for unit n+2. We illustrate our method with examples and a simulation study. Our method is fully adaptive to available data, providing an alternative to the classical approach where the probability distribution of a unit's time to failure is assumed to be known. We discuss the possible use of our method and compare it with the classical approach, where we conclude that in most situations our adaptive method performs very well, but that counter-intuitive results can occur.

Journal Article Type Article
Publication Date 2006-01
Deposit Date Nov 18, 2008
Journal Journal of the Operational Research Society
Print ISSN 0160-5682
Electronic ISSN 1476-9360
Publisher Taylor and Francis Group
Peer Reviewed Peer Reviewed
Volume 57
Issue 1
Pages 63-81
Keywords Opportunity-based age replacement, Nonparametric predictive inference, Renewal reward theorem.
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