An integrated framework of preventive maintenance and task scheduling for repairable multi-unit systems

Abstract

Preventive maintenance and task scheduling are both crucial activities in industrial practice. Although they are interdependent and mutually influential, most existing studies typically analyze them separately. In this paper, an integrated framework of preventive maintenance planning and task scheduling is explored. On one hand, while most scholars focus on the system as a whole in scheduling studies, we further take into account the degradation and maintenance of multiple units during the task scheduling process. On the other hand, instead of only using "direct replacement" as the main maintenance method, we further consider the repairability of the unit by incorporating imperfect maintenance effects into the maintenance modeling. Additionally, the lifecycle partitioning method is proposed to analyze the maintenance groups for multiple units at the completion of scheduling tasks and their corresponding probabilities. Based on this foundation, an integrated decision model is established with the preventive maintenance threshold and scheduling task sequence as decision variables to minimize the total weighted expected completion time. Finally, a novel genetic algorithm based on hybrid encoding is proposed, and the effectiveness of integrated decision-making was validated using a practical example.