Please use this identifier to cite or link to this item: https://doi.org/10.1109/TR.2017.2778283
Title: Optimal Inspection and Replacement Policies for Multi-Unit Systems Subject to Degradation
Authors: Qiuzhuang Sun 
Zhisheng Ye 
Nan Chen 
Keywords: Condition-based maintenance (CBM)
Control limit policy
K-out-of-N: G systems
Markov decision process
Wiener process
Issue Date: 25-Dec-2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Citation: Qiuzhuang Sun, Zhisheng Ye, Nan Chen (2017-12-25). Optimal Inspection and Replacement Policies for Multi-Unit Systems Subject to Degradation. IEEE Transactions on Reliability 67 (1) : 404-413. ScholarBank@NUS Repository. https://doi.org/10.1109/TR.2017.2778283
Abstract: Condition-based maintenance (CBM) is proved to be effective in reducing the long-run operational cost for a system subject to degradation failure. Most existing research on CBM focuses on single-unit systems where the whole system is treated as a black box. However, a system usually consists of a number of components and each component has its failure behavior. When degradation of the components is observable, CBM can be applied to the component level to improve the maintenance efficiency. This paper aims to study the optimal inspection/replacement CBM strategy for a multi-unit system. Degradation of each component is assumed to follow a Wiener process and periodic inspection is considered. We cast the problem into a Markov decision framework and derive the optimal maintenance decisions that minimize the maintenance cost. To better illustrate the optimal maintenance strategy, we start from a 1-out-of-2: G system and show that the optimal maintenance policy is a two-dimensional control limit policy. The argument used in the 1-out-of-2: G system can be readily extended to general cases in a similar way. The value iteration algorithm is used to find the optimal control limits, and the optimal inspection interval is subsequently determined through a one-dimensional search. A numerical study and a comprehensive sensitivity analysis are provided to illustrate the optimal maintenance strategy.
Source Title: IEEE Transactions on Reliability
URI: https://scholarbank.nus.edu.sg/handle/10635/168377
ISSN: 00189529
DOI: 10.1109/TR.2017.2778283
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