Wonjoo Lee
Papers
1
Total Citations
23
H-Index
1
About
Wonjoo Lee is a leading researcher in advanced manufacturing and intelligent welding systems, with a primary focus on real-time quality monitoring and process automation. His most cited work, "Prediction of internal welding penetration based on IR thermal image supported by machine vision and ANN-model during automatic robot welding process" (2024, 23 citations), addresses a critical challenge in welding technology: the need for objective, timely, and cost-effective quality assessment. Lee’s major contribution lies in integrating infrared thermal imaging with machine vision and artificial neural networks (ANN) to enable non-invasive, real-time prediction of weld penetration depth during robotic welding. This approach overcomes the limitations of traditional post-process inspection methods, which are often subjective and inefficient. By developing a data-driven model that learns from thermal signatures, Lee has paved the way for smarter, self-optimizing welding systems. His work holds significant implications for industries such as automotive, shipbuilding, and aerospace, where weld integrity is paramount. With growing citations reflecting its practical impact, Lee’s research continues to advance the frontier of intelligent manufacturing, offering a robust framework for automated quality control in complex production environments.
Research Focus
Key Achievements
Top Papers
- 1