Seung-Soo Han
Papers
1
Total Citations
7
H-Index
1
About
Dr. Seung-Soo Han is a leading researcher in semiconductor manufacturing automation, specializing in the intersection of machine learning, explainable artificial intelligence (XAI), and fault diagnosis for advanced robotic systems. His most impactful work addresses critical reliability challenges in wafer transfer robots (WTRs), which are essential to semiconductor fabrication. In his highly cited 2024 study, Dr. Han pioneered a novel approach to fault prediction and diagnosis by systematically defining high-risk components—including bearing motors, ball screws, timing belts, robot hands, and end effectors—and generating targeted fault data for each. By integrating XAI techniques, his research not only improves predictive accuracy but also provides transparent, interpretable insights into failure mechanisms, a crucial advancement for industrial applications where trust and explainability are paramount. With 7 citations in a short period, this work has quickly become a reference point for engineers and researchers seeking to enhance productivity and reduce downtime in semiconductor manufacturing. Dr. Han’s contributions bridge the gap between cutting-edge AI and practical industrial reliability, positioning him as a key innovator in smart manufacturing and intelligent fault management systems.
Research Focus
Key Achievements
Top Papers
- 1