A New Bottleneck Identification Method of Re-Entrant Manufacturing System Based on Complex Networks

Bottleneck identification is a core aspect of manufacturing system control and scheduling. Re-entrant manufacturing systems are costly and slow when using traditional methods for bottleneck identification. In this paper, we proposed a bottleneck identification method for re-entrant manufacturing systems based on the topology of neighboring nodes and the centrality of gravity, which effectively reduces the computational cost and accelerates the identification speed. The effectiveness of the method is verified by comparing with the results of the system simulation method. This method can provide a new idea for the rapid scheduling control of large-scale intelligent manufacturing systems.