During the production scheduling process, equipment degradation occurs gradually due to the influence of processing objects and external factors. Maintenance serves as an effective means to restore system performance. Most existing studies assume that pre-planned maintenance can be executed on time. However, maintenance arrivals are often delayed due to factors such as stochastic equipment degradation and limited maintenance resources. In this study, we propose a novel perspective-dependent maintenance policy that considers proactive maintenance preparation. This policy enables maintenance preparation work to be conducted simultaneously with production scheduling tasks, ensuring timely completion of arriving maintenance and reducing downtime waiting time. Preventive warning thresholds and scheduling sequences are considered as decision variables to minimize the total weighted expected completion time during job scheduling horizon. Furthermore, the relationship between maintenance preparation time and processing time is analyzed, and the probabilities of completing maintenance preparation at different stages are derived. Finally, through a comparison with traditional strategies that do not consider maintenance preparation time and a sensitivity analysis of relevant parameters, the correctness and effectiveness of the integrated decision model are validated.
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