Abstract

This paper proposes a new joint production, maintenance, and dynamic sampling inspection control policy, for failure-prone manufacturing systems. The integrated policy help decision-makers to find both production rate and maintenance frequency, as well as the size of the sample to be inspected. The inspection policy is based on a dynamic sampling plan, which adapts the sample size according to the system degradation and takes into account the interactions between production, maintenance, and quality control. To optimize jointly the integrated policy's control settings, a comprehensive and thorough mathematical model is developed to capture the complex dynamic and stochastic behavior of the manufacturing system. The proposed model relaxes several simplifying assumptions so that reliability and quality degradations are operation-dependent, duration and cost of inspection are non-negligible, no restriction on random distributions and failures occur at any time, as in the real manufacturing world. Besides, a new signal-based simulation model is developed and a detailed sensitivity analysis is carried out to validate analytical results. The results show the relevance of the analytical approach and help us to prove the importance of adapting the inspection effort to the inner quality in the production. An extended comparative study is provided and shows that the proposed integrated policy, based on dynamic inspection, outperforms those based on classical inspection strategies considered in the literature and practice.

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