Purpose – The purpose of this paper is to develop a bottleneck-based opportunistic maintenance (OM) model for the series production systems with the integration of the imperfect effect into maintenance activities. Design/methodology/approach – On the analysis of availability and maintenance cost, preventive maintenance (PM) models subjected to imperfect maintenance for different equipment types are built. And then, a cost-saving function of OM is established to find out an optimal OM strategy, depending on whether the front-bottleneck machines adopt OM strategy or not. A numerical example is given to show how the proposed bottleneck-based OM model proceeded. Findings – The simulation results indicate that the proposed model is better than the methods to maintain the machines separately and the policy to maintain all machines when bottleneck machine reaches its reliability threshold. Furthermore, the relationship between OM strategy and corresponding parameters is identified through sensitivity analysis. Practical implications – In practical situations, the bottleneck machine always determines the throughput of the whole series production system. Whenever a PM activity is carried out on the bottleneck machine, there will be an opportunity to maintenance other machines. Under such circumstances, findings of this paper can be utilized for the determination of optimal OM policy with the objective of minimizing total maintenance cost of the system. Originality/value – This paper presents a bottleneck-based OM optimization model with the integration of the imperfect effect as a new method to schedule maintenance activities for a series production system with buffers. Furthermore, to the best of the knowledge, this paper presents the first attempt to considering the bottleneck constraint on system capacity and diverse types of machines as a means to minimize the maintenance cost and ensure the system throughput.
SummaryThe buffer allocation problem is an important issue in production lines design. In this paper, we present new evaluation and optimization methods to optimally allocate buffers in unreliable production lines. Through analyzing different states of the machines and buffers by Markov process and incorporating the aggregation method, we make an evaluation on the system availability, instead of the throughput rate of the line. The optimization method is proposed by combining particle swarm optimization and estimation of distribution algorithm to maximize the system availability. It generates the new populations by estimation of distribution algorithm and particle swarm optimization to take their respective advantages in global and local optimization. Numerical tests and simulations are performed to validate the performance of the evaluation and optimization methods. The results indicate the effectiveness and efficiency of the proposed methods.
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