Maintenance analysis of a partial observable K-out-of-N system with load sharing units

In this paper, we consider the inspection and maintenance optimization of a K-out-of-N load-sharing system that operates in a deteriorating working condition. The failure rate of each component depends on its load-sharing and the system working condition. During the operation, the system working condition can be deteriorated from the healthy state to the abnormal state. Both the states of the components and the system working environment are hidden. To ensure the system safety, periodical inspection is implemeted, upon which, two-folds of information can be obtained: the state of each component and the partial revealed information corresponding to the state of the working condition. A maintenance policy is proposed based on the observations. The policy is assessed by the total expected discounted maintenance cost in the long-run horizon. We cast the problem into a partially observable Markov decision process framework. We utilize the value iteration algorithm to solve the inspection and maintenance optimization problem. Sensitivity analyses through numerical examples are carried out. A case study of a parallel system with electric motors is examined to show the applicability of the proposed model.