Collaborative Scheduling for Single-Arm Cluster Tools With an Equipment Front-End Module Subject to Chamber Cleaning Requirements

• Published in: IEEE transactions on systems, man, and cybernetics. Systems Vol. 54; no. 10; pp. 5912 - 5924
• Main Authors: Huang, BaoYing, Song, TaiRan, Wu, NaiQi, Qiao, Yan
• Format: Journal Article
• Language: English
• Published: IEEE 01.10.2024
• Subjects: Cluster tool; Clustering algorithms; Collaboration; equipment front-end module (EFEM); Job shop scheduling; Optimal scheduling; Robot kinematics; scheduling; semiconductor manufacturing; Task analysis
• ISSN: 2168-2216; 2168-2232
• DOI: 10.1109/TSMC.2024.3409727

In semiconductor manufacturing, cluster tools tend to integrate a vacuum module (VM), a loadlock module (LLM), and an equipment front-end module (EFEM). While scheduling techniques exist for cluster tools without EFEM, the collaboration among these modules introduces additional challenges for tools with EFEM. In such tools, LLM acting as a shared module plays a crucial role in operating a cluster tool. Moreover, modern fabs have adopted the practice of chamber cleaning after processing each wafer to eliminate chemical residue that may remain within chambers. This article addresses a cyclic scheduling problem of a single-arm cluster tool with EFEM, while considering chamber cleaning requirements. We propose a conflict-free loadlock (LL) state transformation sequence of One-in and One-out LLs to describe the transformations resulted from LL operations. We then present cooperative strategies for robots to access LLM during the state transformation. Based on these strategies, we derive closed-form algorithms to find feasible and optimal schedules in terms of tool cycle time, allowing for an analysis of the best-performing strategy combinations. The effectiveness of the proposed algorithm is illustrated by experimental results.