Joint production control and maintenance policy for a serial system with quality deterioration and stochastic demand

• Published in: Reliability engineering & system safety Vol. 199; pp. 106918 - 12
• Main Authors: Wang, Lin, Lu, Zhiqiang, Ren, Yifei
• Format: Journal Article
• Language: English
• Published: Barking Elsevier Ltd 01.07.2020; Elsevier BV
• Subjects: Condition-based maintenance; Cost control; Dependence; Deterioration; Dynamic stochastic demand; Economic models; Inspection; Mathematical models; Optimization; Predictive maintenance; Production controls; Quality deterioration; Reliability engineering; Simulation-based optimization; Stochastic dependency; Simulation-based optimization; Condition-based maintenance; Stochastic dependency; Dynamic stochastic demand; Quality deterioration
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2020.106918

•Proposing a predictive maintenance policy based on the stochastic quality deterioration process and non-periodic inspection schedule for the machine.•Modeling the deterioration dependency between the machines in serial system.•Proposing an opportunistic maintenance policy considering both stochastic dependency and economic dependency for the system.•Developing a simulation-based optimization method for the integrated model.•Validating the advantages of the model through comparative experiments. We consider a serial production system subject to stochastic deterioration with usage. Machines in the system will suffer quality failures and produce non-conforming items when they reach the out-of-control state. Non-conforming items transferred into the downstream machines may accelerate their deterioration process. Inspection is performed on the system to detect the state of all machines before starting each production lot. The predictive maintenance policy based on the predictive failure probability of each machine and the production control policy based on the target service level are proposed to meet the dynamic stochastic demand every period. Moreover, an opportunistic maintenance policy is considered to address the stochastic dependency and economic dependency in the system. An integrated model of production, quality and maintenance is developed to minimize the total cost. The optimal joint policy of the model is obtained by a simulation-based optimization method. Numerical experiments validate the advantages of our model in terms of cost savings and service improvement.