Abstract
The work presented in this paper addresses the problem of joint optimization of the production, setup and corrective maintenance activities of a manufacturing system. This system consists of a machine subject to breakdowns and repairs and producing two types of parts. A corrective maintenance strategy whose repair rate depends on the number of setup operations already performed on the production system is considered in this work. The objective of this research is to propose a policy that controls production, setup, and corrective maintenance. The contribution of this paper is through the control of the repair rate, combined with the planning of production and setup in a dynamic and stochastic context. Optimality conditions in the form of Hamilton-Jacoby-Bellman (HJB) equations are obtained and a numerical approach is proposed in order to deal with the joint optimization issues. Extensive simulations are performed to address many scenarios that illustrate the interactions between production, setup and maintenance activities.
Highlights
The work presented in this paper addresses the problem of joint optimization of the production, setup and corrective maintenance activities of a manufacturing system
Depending on the state of the system defined by the levels of machine deterioration and by the quality of the parts produced, Njike et al [3] and Rivera-Gomez et al [4] developed joint optimization models in an uncertain environment and contributed to the development of new decision support tools for uncertain manufacturing systems
A joint optimization of production, setup and maintenance policies based on stochastic dynamic programming and numerical methods was presented by Boukas and Kenne [6] in a dynamic context
Summary
The work presented in this paper addresses the problem of joint optimization of the production, setup and corrective maintenance activities of a manufacturing system. This system consists of a machine subject to breakdowns and repairs and producing two types of parts. In order to determine the optimal production policies for different classes of manufacturing systems subject to breakdowns and random repairs, Berthaut et al [10] have developed preventive maintenance strategies regardless of production. They have shown the benefits of combining
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