Joint optimization of preventive maintenance and production rescheduling with new machine insertion and processing speed selection. (April 2022)

• Record Type: Journal Article
• Authors: An, Youjun; Chen, Xiaohui; Hu, Jiawen; Zhang, Lin; Li, Yinghe; Jiang, Junwei
• Is Part Of: Reliability engineering & system safety. Volume 220(2022)
• Publication Date: 2022-04
• Subjects: Preventive maintenance -- Flexible job-shop rescheduling -- New machine insertion -- Processing speed selection -- Bi-population cooperative evolutionary algorithm; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2021.108269
• Languages: English
• ISSNs: 0951-8320

Abstract

Abstract: With the continuous improvement of machine performance, the multifunction machine has gradually become the first choice of many enterprises. Due to the usage and wearing of the machine, the successive operating times will decrease, while the consecutive maintenance durations will increase. Under these contexts, this paper focus on the joint optimization of preventive maintenance and flexible job-shop rescheduling with processing speed selection, and the dynamic arrival of the new machine is considered to enhance productivity. Specifically, (1) a bivariate maintenance policy considering processing speed is proposed to develop a reasonable maintenance plan for each machine; and (2) for evaluating, responding and optimizing the dynamic scheduling problem, a multi-objective optimization model, two rescheduling strategies and a bi-population cooperative evolutionary algorithm are separately constructed. In numerical experiments, the Taguchi method is first employed to set the parameters of the proposed algorithm. Second, the superiority of the proposed migration rescheduling strategy is demonstrated by comparing complete rescheduling strategy. Third, the effectiveness of the improved operators and the proposed algorithm is verified by algorithm comparison. Next, the benefits of the selectable processing speed are proven by comparing with the nominal processing speed. Finally, a sensitivity analysis on the processing speed optional range is performed. Highlights: A new rescheduling problem with new machine insertion is considered. Two rescheduling strategies are designed to respond to the dynamic event. A bivariate maintenance policy with processing speed selection is constructed. The coupling relationship between production and maintenance is explored. A bi-population cooperative evolutionary algorithm (BCEA) is proposed.