Joint optimization of preventive maintenance and production rescheduling with new machine insertion and processing speed selection

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.