Dynamic health management decision-making for fleet based on selective maintenance

Prognostics and health management (PHM), as an advanced predictive maintenance method, has become a hot research topic of equipment support. To solve the problem that the existed PHM systems cannot yield dynamic and timely results of health management decision-making, a novel selective maintenance (SM) based model was developed to obtain the optimal decisions, including the optimal maintenance strategies, maintenance task assignment, quantity of spare part ordered, optimal equipment task scheduling, etc. In this model, the imperfect maintenance options, multiple resource constraints, such as personnel, time, cost, etc., spare part ordering and task scheduling, were considered simultaneously. Based on the theory of selective maintenance, a dynamic health management decision-making model was established, and an optimal scheme, which includes optimal maintenance strategies, maintenance task scheduling, number of spare spart ordering, and optimal task planning, is obtained. Finally, an illustrative example was presented to verify the effectiveness of the proposed model, and the effect of the maintenance personnel number, spare part number and mission scheduling on decisions were analyzed. The results showed that the proposed model was of great significance for supporting equipment health management practice and improving the maintenance quality and effectiveness. © 2024 Chinese Institute of Electronics. All rights reserved.