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. Different wafer types may have different processing routes, which causes deadlocks and complicates the scheduling problem of cluster tools. This work aims to develop 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 productivity, 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.