A real-time variable cost-based maintenance model from prognostic information

With advances in condition monitoring technologies, the past decade has witnessed an increasingly growing research interest on various aspects of condition based maintenance with prognostic information. Most of these maintenance policies in the literature are evaluated with only the mean maintenance cost. However, it is well known that maintenance cost varies substantially and using a mean cost could lead to over or under budgeting with high consequences of risks. In this paper, we develop a new method to consider the effects of both the expectation of the maintenance cost and its variability. Given the prognostic information obtained from condition monitoring and variable maintenance cost, we obtain a maintenance decision which is different from that of the mean maintenance cost based model under the same setting. The prognostic information is obtained from a degradation process modelled as an adaptive Wiener process in real time. One important proposition obtained shows that the decision from the proposed model is conservative as opposed to the case considering the mean cost only. We demonstrate the proposed method with a practical case study. The results indicate that our method can effectively mitigate the management risk, but with a small cost increase.