Bottleneck detection for discrete manufacturing system based on object-oriented colored petri nets and cloud simulation

Abstract

To identify the bottleneck unit of discrete manufacturing system dynamically, an intelligent detection method of bottleneck (IDMOB) is proposed by combining object-oriented colored Petri nets (OOCPN) and cloud simulation. With the proposed method, the production cells of manufacturing system are abstracted as several Petri net sub-modules. And the messages are passed through mapping functions and message passing gates among Petri net modules. Then, the cloud simulation is created to simulate the real processing, and the production data and capacity function are plugged into the cloud to detect the bottleneck unit intelligently. Finally, the effectiveness of IDMOB method is applied and validated in a practical case study from the power transformer industry.