Optimal maintenance policy for multi-component systems under Markovian environment changes

• Published in: Expert systems with applications 2013-12, Vol.40 (18), p.7391-7399
• Main Authors: Zhang, Zhuoqi, Wu, Su, Li, Binfeng, Lee, Seungchul
• Format: Article
• Language: English
• Subjects: Applied sciences; Decision theory. Utility theory; Deterioration; Environmental influence; Exact sciences and technology; Industrial metrology. Testing; Inventory control, production control. Distribution; Iterative methods; Maintenance; Maintenance policy; Markov decision processes; Markov processes; Mathematical analysis; Mathematical models; Mathematics; Mechanical engineering. Machine design; Multi-component system; Operational research and scientific management; Operational research. Management science; Opportunistic maintenance; Optimization; Policies; Probability and statistics; Probability theory and stochastic processes; Sciences and techniques of general use
• ISSN: 0957-4174; 1873-6793
• DOI: 10.1016/j.eswa.2013.07.003

•Maintenance model for multi-component systems under environmental influence.•Opportunity maintenance consideration in multi-component systems.•Mathematical proof of existence and optimality of a (nr,Nr) type policy.•Iterative approximation algorithm for maintenance policy in multi-component systems. In this paper, we study multi-component systems, which environmental conditions and opportunistic maintenance (OM) involve. Environmental conditions will exert an influence on deterioration processes of the components in the system. For each component, the worse the environmental conditions are, the faster its deterioration speed is. We want to determine when to preventively maintain each component under such environmental influence. Our purpose is to minimize its long-run average maintenance cost. We decompose such a multi-component system into mutually influential single-component systems, and formulate the maintenance problem of each component as a Markov decision process (MDP). Under some reasonable assumptions, we prove the existence of the optimal (nr,Nr) type policy for each component. A policy iteration method is used to calculate its optimal maintenance policy. Based on the method, we develop an iterative approximation algorithm to obtain an acceptable maintenance policy for a multi-component system. Numerical examples find that environmental conditions and OM pose significant effects on a maintenance policy.