a novel approach for planning imperfect preventive maintenance in manufacturing systems by a simulation-optimization approach

This study addresses simulating manufacturing processes and maintenance activities in a multi-product industry to model the complexity of interactions between maintenance strategies and their effects on a manufacturing system. a novel simulation model has been developed using discrete event simulation (des) to investigate interactions between manufacturing and maintenance systems. a real two-product manufacturing line in an automotive factory was studied to demonstrate the proposed model’s efficacy. two significant challenges were considering preventative maintenance (pm) as imperfect pm activities and estimating unknown probability distribution in a real industry. these are new assumptions that generally have not been considered in the prior studies. to overcome these problems, imperfect maintenance activities are defined as different scenarios and unknown probability distributions are estimated based on historical records in the case study. a simulation-based optimization method was developed using optquest, and the results of the proposed method were then compared with the current values in the case study. the findings illustrate that the proposed model can reduce the system’s manufacturing and maintenance costs by 13%. in addition, the implementation of maintenance planning in this research improved some factors in the manufacturing system efficiently.