Investigation on distributed rescheduling with cutting tool maintenance based on NSGA-III in large-scale panel furniture intelligent manufacturing

With the bloom of the customized panel furniture market, its production scheduling system is facing more and more challenges in getting intelligent due to real-world constraints, such as distributed manufacturing, the contradiction between machining efficiency and energy consumption of production, the inevitable cutting tool degradation, and machine failure. In order to address this complicated scheduling problem, this paper proposes an integrated multi-objective optimization model based on non-dominated sorting genetic algorithm III (NSGA-III). More precisely, the leading innovative works are presented as follows: (1) a factory allocation strategy is designed to find the optimal quantity distribution of jobs between factories; (2) a cutting tool maintenance activity is inserted before the operation of a job when the remaining useful life of the tool run out on a machine; (3) a modified right-shift rescheduling method is proposed to improve the machine utilization rate of parallel machines. In the numerical simulation, the superiority of NSGA-III is verified by a performance test. Second, in the real-world case study of panel furniture manufacturing, the competitiveness of the proposed factory allocation strategy is demonstrated by comparing it with the currently used in the factory. Finally, the modified right-shift rescheduling method outperformed others in energy reduction through real-world instances.