A novel maintenance strategy for manufacturing system considering working schedule and imperfect maintenance

Condition-based maintenance (CBM) strategies that consider product quality lack a thorough analysis of the impact of manufacturing enterprise's working schedule, which does not align with real-life production scenarios. To address this gap, this study proposes a novel CBM strategy model for manufacturing systems that takes into account working schedule to determine the optimal balance between maintenance and production while considering product quality. The maintenance set includes imperfect maintenance and perfect maintenance to capture real-life manufacturing scenarios. The model establishes an optimal maintenance strategy using a Markov decision process (MDP) framework. A numerical study is conducted based on internal information and data collected by sensors from a commercial vehicle manufacturing enterprise to demonstrate the effectiveness of the proposed strategy. We proposed a dual-value iteration algorithm to solve the MDP model. Finally, a comprehensive sensitivity analysis is performed to investigate the impact of cost-related parameters on the strategy.