Abstract
Machine tools, like any other system, are designed with the best possible reliability under given budget, time, and technology constraints. Appropriate maintenance policies are deployed to sustain reliability performance over the life of the system. From the operational perspective, the reliability performance of machine tools is not only dependent on inherent reliability and maintenance, but also significantly influenced by peripheral functions such as production planning and material supply decisions, etc. Moreover, the interaction effect of these functions with inherent reliability and maintenance policy makes the machine tools reliability modeling a complex problem. A holistic (considering various aspects together) and integrated (parametric-level consideration) approach is thus needed to optimize the performance of machine tools. The present paper aims to holistically consider machine tool reliability, maintenance, production, and material supply aspects to simultaneously optimize various decisions related to these functions. For pragmatic manifestation, a real manufacturing environment is considered, which is characterized by the stochastic nature of various functions and associated uncertainties. Furthermore, an exhaustive evaluation is performed over a broad range of manufacturing environment to demonstrate the superiority of the proposed approach.
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