Papers
9
Total Citations
259
H-Index
9
About
Tae-Sun Yu is a leading researcher in semiconductor manufacturing automation, with a focus on optimizing cluster tools—the robotic systems central to wafer fabrication. His work addresses critical challenges arising from shrinking circuit widths below 20 nanometers, which demand stringent process control. Yu’s major contributions include pioneering scheduling algorithms for both single-armed and dual-armed cluster tools that incorporate chamber cleaning (purge) operations, a necessity for removing chemical residuals to prevent quality failures. His 2017 papers on this topic have garnered 61 and 59 citations, respectively, establishing foundational knowledge in the field. He has also advanced the handling of wafer delay constraints, developing adaptive schedules and interference-free sequences to mitigate quality degradation from residual gases and heat. Notable achievements include his 2022 work on cleaning plan optimization for general chamber cleaning periods (29 citations) and a 2023 comprehensive overview in *Semiconductor Manufacturing Automation*. With over 200 total citations, Yu’s research directly impacts real-world fab productivity and yield, making him a key figure for students and engineers tackling the complexities of modern semiconductor fabrication.
Research Focus
Key Achievements
Top Papers
- 1Scheduling Single-Armed Cluster Tools With Chamber Cleaning Operations61 citations · 2017
- 2Scheduling Dual-Armed Cluster Tools With Chamber Cleaning Operations59 citations · 2017
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- 8Semiconductor Manufacturing Automation12 citations · 2023
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