Decomposition in automatic generation of Petri nets for manufacturing system control and scheduling

Document Type


Peer Reviewed


Publication Date


Journal/Book/Conference Title

International Journal of Production Research

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End Page



Despite the efforts in developing Petri net models for manufacturing control and scheduling, the generation of Petri net models cannot be automated for agile manufacturing control and scheduling without difficulties. The problems lie in the complexity of Petri net models. First of all, it is difficult to visualize the basic manufacturing process flow in a complex Petri net model even for a Petri net modelling expert. The second problem is related to the complexity of using Petri net models for manufacturing system scheduling. In this paper, a decomposition methodology in automatic generation of Petri nets for manufacturing system control and scheduling is developed. The decomposition methodology includes representing a manufacturing process with the Integrated Definition 3 (IDEF3) methodology, decomposing the manufacturing process based on the similarity of resources, transforming the IDEF3 model into a Petri net control model, and aggregating sub Petri net models. Specifically, a sequential cluster identification algorithm is developed to decompose a manufacturing system represented as an IDEF3 model. The methodology is illustrated with a flexible disassembly cell example. The computational experience shows that the methodology developed in this paper reduces the computational time complexity of the scheduling problem without significantly affecting the solution quality obtained by a simulated annealing scheduling algorithm. The advantages of the methodology developed in this paper include the combined benefits of simplicity of the IDEF3 representation of manufacturing processes and analytical and control properties of Petri net models. The IDEF3 representation of a manufacturing process enhances the man-machine interface.



Published Article/Book Citation

International Journal of Production Research, 38:6 (2000) pp.1437-1457.

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