Maintenance strategy optimization using a continuous-state partially observable semi-Markov decision process

被引:11
|
作者
Zhou, Yifan [1 ]
Ma, Lin [1 ]
Mathew, Joseph [1 ]
Sun, Yong [1 ]
Wolff, Rodney [2 ]
机构
[1] Queensland Univ Technol, Sch Engn Syst, CRC Integrated Engn Asset Management CIEAM, Brisbane, Qld 4001, Australia
[2] Queensland Univ Technol, Sch Math Sci, Brisbane, Qld 4001, Australia
关键词
POLICIES; INSPECTIONS; SYSTEMS;
D O I
10.1016/j.microrel.2010.09.023
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Due to the limitation of current condition monitoring technologies, the estimates of asset health states may contain some uncertainties. A maintenance strategy ignoring this uncertainty of asset health state can cause additional costs or downtime. The partially observable Markov decision process (POMDP) is a commonly used approach to derive optimal maintenance strategies when asset health inspections are imperfect. However, existing applications of the POMDP to maintenance decision-making largely adopt the discrete time and state assumptions. The discrete-time assumption requires the health state transitions and maintenance activities only happen at discrete epochs, which cannot model the failure time accurately and is not cost-effective. The discrete health state assumption, on the other hand, may not be elaborate enough to improve the effectiveness of maintenance. To address these limitations, this paper proposes a continuous state partially observable semi-Markov decision process (POSMDP). An algorithm that combines the Monte Carlo-based density projection method and the policy iteration is developed to solve the POSMDP. Different types of maintenance activities (i.e., inspections, replacement, and imperfect maintenance) are considered in this paper. The next maintenance action and the corresponding waiting durations are optimized jointly to minimize the long-run expected cost per unit time and availability. The result of simulation studies shows that the proposed maintenance optimization approach is more cost-effective than maintenance strategies derived by another two approximate methods, when regular inspection intervals are adopted. The simulation study also shows that the maintenance cost can be further reduced by developing maintenance strategies with state-dependent maintenance intervals using the POSMDP. In addition, during the simulation studies the proposed POSMDP shows the ability to adopt a cost-effective strategy structure when multiple types of maintenance activities are involved. (C) 2010 Elsevier Ltd. All rights reserved.
引用
收藏
页码:300 / 309
页数:10
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