Ting Qu
Papers
2
Total Citations
46
H-Index
2
About
Ting Qu is a leading researcher in semiconductor manufacturing automation, with a primary focus on the modeling, scheduling, and optimization of cluster tools using Petri nets and linear programming. Their work addresses critical challenges in wafer fabrication, particularly the time-constrained scheduling of single-robot-arm cluster tools—a problem essential for improving throughput and ensuring quality in chip production. Qu’s most cited paper (2017, 37 citations) develops a novel approach for optimal cyclic scheduling under wafer residency time constraints, advancing beyond traditional backward strategies to handle more complex, general cases. Another influential study (2017, 9 citations) tackles the daunting task of finding optimal one-wafer cyclic schedules for transport-dominant single-arm multi-cluster tools, a widely adopted configuration in the industry. By integrating Petri net modeling with linear programming, Qu provides efficient, deterministic solutions that significantly enhance tool performance and reliability. Their contributions are vital for both theoretical advances in discrete event systems and practical applications in semiconductor fabs, making them a key figure in optimizing high-tech manufacturing processes.
Research Focus
Key Achievements
Top Papers
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