Optimization of preventive maintenance for a multi-state degraded system by monitoring component performance

Chao-Hui Huang () and Chun-Ho Wang
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Chao-Hui Huang: National Defense University
Chun-Ho Wang: National Defense University

Journal of Intelligent Manufacturing, 2016, vol. 27, issue 6, No 2, 1170 pages

Abstract: Abstract This study aims to construct an optimal preventive maintenance model for a multi-state degraded system under the condition that individual components or sub-systems can be monitored in real time. Given the requirement of minimum system availability, the total maintenance cost is minimized by determining the maintenance activities of components in degraded states. The general non-homogeneous continuous-time Markov model (NHCTMM) and its analogous Markov reward model (NHCTMRM) are used to quantify the intensity of state transitions during the degradation process, allowing the determination of various performance indicators. The bound approximation approach is applied to solve the established NHCTMMs and NHCTMRMs, thus obtaining instantaneous system state probabilities to overcome their inherent computational difficulties. Furthermore, this study utilizes a genetic algorithm to optimize the proposed model. A simulation illustrates the feasibility and practicability of the proposed approach.

Keywords: Multi-state degraded system; Preventive maintenance; Non-homogeneous continuous-time Markov models; Genetic algorithm; Bound approximation approach (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10845-014-0940-5

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