Modeling and Scheduling of Dual-Arm Cluster Tools With Multifunctional Process Modules

In semiconductor manufacturing, a multifunctional process module (MPM) can perform multiple processing steps by adjusting its functional settings. This enhances the reconfigurability of cluster tools and allows them to flexibly adapt to diverse production requirements. However, the different function settings of the MPM change the number of processing modules and generate multiple alternative processing routes. Deadlocks occur more frequently in wafer manufacturing processes with flexible routes. The flexible configuration of MPM function leads to a highly complex and large-scale model. Proper configuration of MPM can optimize lot scheduling and improve processing efficiency. Thus, based on the functional setting of MPM, process-oriented Petri nets (POPNs) are established to describe the transient and steady state processing of the system, and control explanations are developed to avoid the system deadlock. Then, based on the evolving mechanism of the Petri nets, the temporal properties of the system under the earliest starting strategy (ESS) are analyzed. An algorithm based on ESS is developed to compute the makespan of wafers in a lot and optimize the settings of the MPM function. Experimental results demonstrate that for scheduling problems unsolvable by the mixed-integer programming (MIP) model, the algorithm can adaptively minimize system lot completion time by reasonably setting the function of MPM.