Yongho Lee
Papers
1
Total Citations
28
H-Index
1
About
Yongho Lee is a leading researcher in intelligent manufacturing and robotic welding systems, with a primary focus on real-time process monitoring and quality control. His most notable contribution is the development of a data-driven, real-time diagnosis framework for detecting angular misalignment in robot spot-welding systems, a critical issue that can cause severe weld defects like porosity. By integrating machine learning with voltage and current sensor data, Lee’s work enables online monitoring that significantly enhances weld nugget quality and system reliability. His 2020 paper on this topic has garnered 28 citations, reflecting its practical impact on smart manufacturing. Lee’s research bridges the gap between traditional welding engineering and advanced artificial intelligence, offering scalable solutions for industrial automation. His achievements are particularly valuable for students and researchers exploring non-destructive evaluation and predictive maintenance in robotic systems. Through his innovative approach, Lee is helping to define the future of adaptive, self-diagnosing manufacturing processes.
Research Focus
Key Achievements
Top Papers
- 1