Scheduling dual-armed cluster tools with cleaning processes

Modern cluster tools tend to clean the chambers each time a specified number of wafers have been processed. Such cleaning processes are intended to reduce the quality risk due to the residual chemicals within the chambers. When such cleaning processes are introduced, the conventional scheduling methods for cluster tools, such as the swap sequence for dual-armed cluster tools, are no longer effective. Therefore, we examine a cyclic scheduling problem for a dual-armed cluster tool that performs cleaning processes periodically. We first identify sufficient conditions for which the conventional backward and swap sequences give the minimum cycle time. We then develop a systematic way of generating all feasible robot task sequences, for which the cycle times can be computed. However, the number of feasible robot task sequences increases too fast to be enumerated as the cleaning cycle and the number of process steps increase. To address the complexity problem, we propose two heuristic scheduling strategies and compare them with the conventional scheduling methods and the lower bound of each schedule, respectively, to verify their effectiveness experimentally.