An effective scheduling method to single-arm cluster tools for processing multiple wafer types

Recently, in semiconductor manufacturing, cluster tools have to process multiple wafer types concurrently due to product customization. Dif-ferent wafer types may have different processing routes, which causes deadlocks and complicates the scheduling problem of cluster tools. This work aims to de-velop a general method to resolve the scheduling problem of single-arm cluster tools with a general mix of wafer types. To this end, a generic Petri net model controlled by self-loops is developed to optimally avoid deadlocks. Based on the Petri net model, an earliest starting strategy is adopted to operate single-arm cluster tools once wafers enter the tools. In order to maximize the productiv-ity, a particle swarm optimization algorithm is constructed to determine the releasing sequence of raw wafers. Numerical examples are provided to validate the effectiveness and efficiency of the proposed method.