Condition-based Maintenance and Spare Parts Ordering Strategy Considering the Influence of Condition Detection

Abstract

Aiming at the problem of on-demand maintenance and spare parts ordering under the condition of periodic state detection, a joint decision model of on-demand maintenance and spare parts ordering of single-component system with nonlinear adaptive Wiener process considering the influence of state detection is proposed. Firstly, nonlinear adaptive Wiener process and normal distribution are used to describe the effects of natural degradation process and periodic state detection on equipment degradation, respectively, and the probability distribution of remaining useful life is derived under the first arrival time. Based on the prediction results of remaining useful life, a joint decision-making model of condition-based maintenance and spare parts ordering is established, which aims at minimizing the long-term average cost of components. Finally, an example is given to verify the effectiveness of the proposed method.