Novel approach for machine tool maintenance modelling and optimization using fleet system architecture

In this paper, a novel approach is developed for machine tool maintenance modelling considering fleet system architecture. The fleet system architecture consisting of different types of machine tools from various OEMs operated at different users, but supported by a single repair depot is considered. The prime objective of this paper is to jointly optimize the decisions of Level of Repair (LOR) i.e. repair/move/discard, and Preventive Maintenance (PM) schedules considering user's cost structure and shop floor policy parameters. It is observed that integrated PM and LOR approach gives better Life Cycle Cost (LCC) performance compared to isolated approaches. Also, the importance of user's cost structure and shop floor operations policy parameters in LOR and PM planning is evident from the results. The proposed approach is very useful for the machine tool manufacturers (i.e. OEM) who want to engage into long term maintenance contract with their customers. Integrating LOR and PM is a complex problem. The complexity further increases due to consideration of time dependent failure rate of the machine components, imperfect maintenance which brings partial restoration to the components/systems, and stochastic natures of model parameters. Consequently, a simulation based genetic algorithm approach is used to solve the problem.