Multiple-Time Reentrant Processes Optimization of Robotic Dual-Arm Cluster Tools With Cleaning Operations

Cluster tools are the key equipment in semiconductors manufacturing. Such a tool has been used for some reentrant wafer fabrication processes, such as atomic layer deposition and plasma enhanced chemical vapor deposition. With reentrant processes, wafers need to visit some processing modules for multiple times. This makes a cluster tool no longer a flow-shop system. To ensure the wafer quality, cleaning operations are required by process modules to eliminate the residual gas and chemicals, which complicates the scheduling problem of a cluster tool for reentrant processes. This work focuses on dealing with the challenging scheduling problem of dual-arm cluster tools with cleaning operation for multiple-time reentrant processes. To do so, by analyzing the robot tasks of a tool under the conventional swap strategy, it is found that significant robot delay time is caused by cleaning operation during the swap operation. Thus, to reduce such robot delay time, two novel scheduling strategies are proposed. Based on them, two efficient algorithms are developed to obtain the makespan for completing a given number of wafers. Finally, experiments are carried out to demonstrate the effectiveness of the proposed methods.