Wafer sojourn time fluctuation analysis for time-constrained dual-arm multi-cluster tools with activity time variation

ABSTRACT

In semiconductor manufacturing systems, a time-constrained multi-cluster tool should be scheduled such that a wafer stays in a process chamber in a given time range to satisfy a wafer residency time constraint. In practice, activity time is subject to variation. It could lead to some fluctuation of wafer residency time in a process chamber. Hence, it is crucial to analyze how wafer residency time varies with activity time variation. This issue is especially challenging for multi-cluster tools. This work focuses on determining the exact upper bound of wafer sojourn time delay resulted from activity time variation for dual-arm multi-cluster tools. After discussing their dynamic behaviours, it presents a two-level real-time operational architecture and a real-time control policy. Based on them, this work derives for the first time an efficient algorithm to calculate the exact upper bound of wafer sojourn time delay in a process chamber. As a result, engineers can test whether a given schedule is feasible. Several examples of industrial significance are used to demonstrate the application of the proposed approach.

KEYWORDS:

• Semiconductor manufacturing systems
• multi-cluster tools
• wafer residency time constraint
• real-time scheduling

Acknowledgments

This work is funded in part by Science and Technology development fund (FDCT), Macau SAR (file nos. 0017/2019/A1 and 005/2018/A1), in part by the National Natural Science Foundation of China (NSFC) [61803397]; in part by the Alexander von Humboldt Foundation, and in part by the Open Project of State Key Lab of Digital Manufacturing Equipment & Technology under Grant DMETKF2019015.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work is funded in part by Science and Technology development fund (FDCT), Macau SAR (file nos. 0017/2019/A1 and 005/2018/A1), in part by the National Natural Science Foundation of China (NSFC) [61803397]; in part by the Alexander von Humboldt Foundation, and in part by the Open Project of State Key Lab of Digital Manufacturing Equipment & Technology under Grant DMETKF2019015.