An optimal configuration method of multi-level manufacturing resources based on community evolution for social manufacturing

Due to the rapid development of social economy and diverse market demands, higher requirements are put forward for the existing manufacturing environment, such as the self-organizing aggregation of manufacturing resources, the business collaboration among enterprises, the process control of all stages in the product lifecycle, and the servitization of manufacturing resources. Despite the current research efforts, some questions remain open, including the active interaction among resources, the optimal configuration of multi-level resources for manufacturing tasks, and the dynamic evolution of communities in manufacturing networks. In order to realize the optimal configuration across different enterprises, in this paper, an overall architecture for the optimal configuration of manufacturing resources based on community evolution was proposed. Under the architecture, unique manufacturing resources were encapsulated to multi-level manufacturing services, and they aggregated together autonomously to accomplish upper-level service demands according to semantic matching. Focusing on the matching efficiency between services and demands, three types of communities were developed for the resource configuration, which was realized by the grey relation analysis, the Louvain algorithm, and the fuzzy comprehensive evaluation. The presented methods were demonstrated by a case of drive-shaft production, and some observations and findings were discussed in detail. The results showed that the proposed methods could benefit both customers and manufacturers, which may promote the implementation of social manufacturing effectively.