Tae-Gyung Lee
Papers
2
Total Citations
55
H-Index
2
About
Tae-Gyung Lee is a leading researcher in semiconductor manufacturing automation, with a primary focus on optimizing the operation of cluster tools—critical equipment used in wafer fabrication. His work addresses two major challenges: chamber cleaning and wafer delay. In his highly cited 2022 paper, Lee developed a cleaning plan optimization method for dual-armed cluster tools with general chamber cleaning periods, reducing quality risks from chemical impurities as circuit widths shrink. His 2019 paper on K-cyclic schedules analyzed worst-case wafer delay, a key factor in preventing quality failures caused by residual gases and heat. With over 55 citations across his top papers, Lee’s contributions are vital for improving yield and efficiency in semiconductor fabs. His research combines scheduling theory with practical manufacturing constraints, offering both analytical insights and actionable solutions. Lee’s work is essential reading for engineers and researchers tackling real-time control and optimization in advanced semiconductor production.
Research Focus
Key Achievements
Top Papers
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- 2