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A condition-based maintenance policy for degrading systems with age- and state-dependent operating cost

Liu, Bin, Wu, Shaomin, Xie, Min, Kuo, Way (2017) A condition-based maintenance policy for degrading systems with age- and state-dependent operating cost. European Journal of Operational Research, 263 (3). pp. 879-887. ISSN 0377-2217. (doi:10.1016/j.ejor.2017.05.006) (KAR id:61614)


Most of the maintenance policies in existing publications assume that no cost is incurred as long as the system can undertake missions while little consideration has been devoted to the operating cost during system operation. However, in practice, the operating cost increases while the system ages and degrades even if a system is in a functioning state. This paper proposes a maintenance policy for a degrading system with age- and state-dependent operating cost, which increases with system age and degradation levels. Under such a setting, a replacement model is first developed to investigate the optimal preventive replacement policy. The replacement model is then extended to a repair-replacement model, in which imperfect repair is assumed to restore the system to the operating condition. Particularly, the repair model with controllable and uncontrollable repair levels is considered separately. The paper proves that the optimal maintenance policy is actually a monotone control limit policy, where the optimal control limits decrease monotonically with system age. Finally, a numerical example along with sensitivity analysis is presented to illustrate the optimal maintenance policy. The proposed model implies a more conservative maintenance policy, compared with the traditional model without the age- and state-dependent operating cost.

Item Type: Article
DOI/Identification number: 10.1016/j.ejor.2017.05.006
Uncontrolled keywords: Condition-based maintenance, age- and state-dependent operating cost, side effect of degradation, control limit policy, repair-replacement model
Subjects: H Social Sciences > HA Statistics > HA33 Management Science
Divisions: Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Shaomin Wu
Date Deposited: 04 May 2017 16:50 UTC
Last Modified: 04 Mar 2024 19:06 UTC
Resource URI: (The current URI for this page, for reference purposes)

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