Reactive scheduling for large-scale manufacturing systems based on hybrid Petri net modeling

This paper presents a new scheduling method for a large-scale production system based on the hierarchical Petri net model, which includes FOHPN and TPN. The method macroscopically tries to find an optimal flow of process in the entire system and microscopically generates the processing sequence, taking into consideration the physical constraints which come from the real shop floor. An automobile production system, equipped with 2 stand-by lines controlled by binary signal, is discussed. At a high level, the FOHPN is used to represent continuous flow in production process of an entire system, and MLDS form is used to control the net dynamics of FOHPN. At a low level, TPN is used to represent production environment of each sub-line in a decentralized manner, and MCT algorithm is applied to find a feasible semi-optimal process sequences for each sub-line. The advantage of the scheduling method is its adaptability for unexpected change of production environment such as processing failure, conveyance delay, and so on. The proposed hierarchical scheduling method is confirmed to be very useful through a numerical experiment.