Dynamic maintenance optimization leveraging real-time status information

Group maintenance is an efficient and cost-optimal approach to ensure the operational availability of diverse industrial devices. Most existing group maintenance models, however, determine replacement/repair executions solely based on single age/ degradation information within pre-specified fixed time intervals, which cannot ensure real-time responsiveness of decision-making. To leverage this research gap, this paper proposes a group maintenance strategy based on real-time updating of component health conditions. To this end, regular inspection is executed followed by global dynamic spare replacement, which constitutes a two-stage group decision-making framework from component to the entire system. The optimal maintenance sequence is solved through dynamic programming algorithm, which enables the dynamic union of preventive replacement and opportunistic replacement. The numerical experiment states the substantial advantages of the proposed model in ensuring operational availability while controlling operational cost.