Flexible Resource Allocation in Intelligent Manufacturing Systems Based on Machine and Worker

In order to achieve the personalized customization of intelligent manufacturing systems and make full use of manufacturing resources for efficient and low-cost production, a method for the rational configuration of machine and worker resources in the production workshop is proposed in this paper. Firstly, a multi-objective optimization mathematical model for resource allocation problems is designed. Satisfactory configuration solutions for multi-objective optimization problems are obtained using an improved differential evolution algorithm. Furthermore, taking into account the actual situations in production, such as urgent orders and machine failures, to achieve a dynamic allocation of workshop resources. Finally, through case analysis, the method proposed in this article is compared with NSGA-II and random generation methods, verifying that the resource allocation method proposed in this article can effectively organize workshop production reasonably and efficiently, achieving efficient and low-cost production.