Optimal control limit policy for age-dependent deteriorating systems under incomplete observations

Abstract

The focus of this study is the optimal decision making problem for an age-dependent deteriorating system in which the deterioration unfolds as a non-stationary Markov process. The true deterioration state of the system cannot be known directly and is assumed to be observed incompletely by a monitor that provides information related to the true deterioration state stochastically. The optimal decision making problem is formulated as a partially observable Markov decision process. The optimal maintenance policy is investigated and the structural properties of the resulting optimal expected cost function are obtained. These structural properties establish the existence of an optimal control limit policy with respect to both the deterioration information vector and the age of the system under intuitively meaningful assumptions. The monotonic property of the control limits is also clarified.

Time series semi-Markov decision process with variable costs for maintenance planning

“…Of the 6 papers, only 4 were used for optimizing the maintenance schedule, they are discussed below. Jin et al (2016) applied partially observable MDPs, which can deal well with the incomplete information coming from the condition monitoring equipment. The methodology allows both nonstationary transition rates as well as variable costs.…”