Transient Scheduling of Dual-Armed Cluster Tools With Concurrent Processing: An MIP Model and a Fast Heuristic
Abstract
Efficient transient scheduling of cluster tools is critical to stable fab-level operations in high-mix, low-volume semiconductor manufacturing. This study investigates the transient scheduling problem of dual-armed cluster tools (DACTs) processing two wafer types concurrently. From an engineering-management perspective, the problem is important because wafer release and robot sequencing decisions affect tool utilization, completion-time predictability, and fab-level responsiveness. A mixed-integer programming model is developed to jointly optimize wafer release order and robot task sequence with the objective of minimizing total completion time. To address the computational intractability of medium- and large-scale instances, a two-combined swap sequence (2-CSS) is proposed. Numerical results show that 2-CSS substantially reduces computation time while incurring only a 5.31% average increase in total completion time. The results also show that DACTs provide substantial throughput benefits over single-armed configurations, with improvements of up to 9.51%. Robustness analysis further shows that the observed dual-arm advantage persists across varying robot loading/unloading times and wafer residency time constraint-to-processing time ratios, while 2-CSS maintains small optimality gaps as the loading/unloading time and the processing time of a selected step vary, even when the system bottleneck shifts between processing steps. These findings can help fab managers evaluate transient schedules more quickly and coordinate tool operations more effectively in high-mix production.