Optimal multi-type inspection policy for systems with imperfect online monitoring

• Published in: Reliability engineering & system safety Vol. 207; p. 107335
• Main Authors: Liu, Xingchen, Sun, Qiuzhuang, Ye, Zhi-Sheng, Yildirim, Murat
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.03.2021
• Subjects: Condition-based maintenance; Gas turbine; Multi-type inspection; Partially observable Markov decision process; Multi-type inspection; Gas turbine; Partially observable Markov decision process; Condition-based maintenance
• ISSN: 0951-8320
• DOI: 10.1016/j.ress.2020.107335

•We construct a new stochastic model considering both multi-type inspections and online monitoring.•We formulate this problem under the framework of a partially observable Markov decision process (POMDP).•Some structural properties are established and proved. Both online monitoring and manual inspection are widely used in identifying a system’s health state, based on which proper preventive maintenance (PM) can be carried out. The existing maintenance optimization models typically consider only online monitoring or a single type of inspection and assume they can perfectly reveal the system’s state. However, the information provided by online monitoring is never perfect, and it needs to be combined with the inspection to identify the system’s health state. Besides, there are usually many types of inspections with different costs and detecting capabilities in real applications. It is hence equally important to decide on when operators should make an inspection and which kind of inspection should be performed based on the information from online monitoring. In this paper, we formulate the multi-type inspection decision-making problem within the partially observable Markov decision process (POMDP) framework. We establish some structural properties for the optimal multi-type inspection policy. The value iteration and the λ-minimization algorithm are combined to obtain the optimal solution. A case study is provided to illustrate the optimal inspection policy and its advantage over some existing policies.