Multi-objective imperfect maintenance optimization for production system with an intermediate buffer. (July 2020) - Liu, Qinming; Dong, Ming; Frank Chen, F.; Liu, Wenyi; Ye, Chunming
Highlights: A joint optimization mathematical model considering maintenance and buffer stock is proposed. The imperfect maintenance is considered in the proposed model. The number of random failures can be obtained based on the renewal process. The heuristic algorithm for the proposed integrated model is used. The experiment data can be obtained from an enterprise, and the presented theory and technique are being used in it. Abstract: In several production systems, buffer stocks are built between consecutive machines to ensure the continuity of supply during interruptions of service caused by breakdowns or planned maintenance actions. However, in previous research, maintenance planning is performed individually without considering buffer stocks. In order to balance the trade-offs between them, in this study, an integrated model of buffer stocks and imperfective preventive maintenance for a production system is proposed. This paper considers a repairable machine subject to random failure for a production system by considering buffer stocks. First, the random failure rate of a machine becomes larger with the increase of the number of random failures. Thus, the renewal process is used to describe the number of random failures. Then, by considering the imperfect maintenance action reduced the age of the machine partially, a mathematical model is developed in order to determine the optimal values of the two decision variables which characterize the proposed maintenance strategy and which are: the size of the buffer stock and the maintenance interval. The optimal values are those which minimize the average total cost per time unit including maintenance cost, inventory holding cost and shortage cost, and satisfy the availability constraint. Finally, a heuristic procedure is used to solve the proposed model, and one experiment is used to evaluate the performance of the proposed methods for joint optimization between buffer stocks and maintenance policy. The results show that the proposed methods have a better performance for the joint optimization problem and can be able to obtain a relatively good solution in a short computation time.