Condition-based maintenance optimization for multi-equipment batch production system based on stochastic demand

In order to facilitate efficient maintenance of batch production systems under the increasingly complex demands of present day, an approach is proposed. This approach addresses maintenance issues of equipment in multi-equipment batch production systems under stochastic demand. First, the method considers distinct equipment degradation characteristics and imperfect maintenance at both the system and equipment levels. It simultaneously employs the mechanism of advancing or delaying maintenance, along with a dual time window opportunity maintenance strategy, to minimize the costs associated with opportunistic maintenance. Then, different models are developed to cater to various scenarios. At the system level, maintenance is conducted through component grouping based on production transition opportunities. At the equipment level, the optimal preventive maintenance cycle duration is determined by calculating the current minimal maintenance cost rate, thus, determining the optimal preventive maintenance timing. The solution methodology employs the Monte Carlo method to simulate the production system across different batches, calculating the actual preventive maintenance timings and total maintenance costs. Finally, by illustrative cases and the optimization of the total cost over the production cycle, the effectiveness of the proposed maintenance strategy for multi-equipment batch production systems under stochastic demand is demonstrated by measuring cost against the frequency of failures.