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http://dx.doi.org/10.5351/CKSS.2006.13.1.191

Bayesian Method on Sequential Preventive Maintenance Problem  

Kim Hee-Soo (School of Aerospace and Naval Architecture, Chosun University)
Kwon Young-Sub (School of Aerospace and Naval Architecture, Chosun University)
Park Dong-Ho (Department of Information and Statistics, Hallym University)
Publication Information
Communications for Statistical Applications and Methods / v.13, no.1, 2006 , pp. 191-204 More about this Journal
Abstract
This paper develops a Bayesian method to derive the optimal sequential preventive maintenance(PM) policy by determining the PM schedules which minimize the mean cost rate. Such PM schedules are derived based on a general sequential imperfect PM model proposed by Lin, Zuo and Yam(2000) and may have unequal length of PM intervals. To apply the Bayesian approach in this problem, we assume that the failure times follow a Weibull distribution and consider some appropriate prior distributions for the scale and shape parameters of the Weibull model. The solution is proved to be finite and unique under some mild conditions. Numerical examples for the proposed optimal sequential PM policy are presented for illustrative purposes.
Keywords
Sequential PM; Bayesian approach; Age reduction; Optimal PM schedule; Hybrid PM model; Prior distribution;
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