Optimal Scheduling of Single-Armed Cluster Tools With Two Wafer Types and Chamber Cleaning

Abstract

Cluster tools (CTs) are extensively utilized in semiconductor manufacturing. To tackle the challenging scheduling problems of CTs that concurrently process two wafer types, studies have been previously conducted based on predetermined robot task sequences, resulting in suboptimality of throughput and low wafer residency time constraint (WRTC)-satisfaction ratio. With both WRTC and chamber cleaning operations taken into account for the first time, this work proposes a deterministic scheduling strategy by drawing on previous studies, as well as a novel and efficient mixed integer programming (MIP) model to determine the optimal release sequence of wafer types and robot task sequence. Compared to the existing deterministic scheduling strategies, computational experiments on large randomly generated instances show that the developed MIP model could improve throughput by 2.63% on average, and enhance the WRTC-satisfaction ratio by at least 108.33% demonstrating its effectiveness and significance.