Ji-Woong Lee
Papers
3
Total Citations
97
H-Index
3
About
Ji-Woong Lee is a leading researcher at the intersection of smart manufacturing, intelligent fault diagnosis, and automated production systems. His work addresses critical challenges in modern industry, particularly the slow transition to automation in labor-intensive sectors and the difficulty of collecting large-scale data for deep learning applications. Lee’s most cited paper (36 citations) pioneers an automated manufacturing process for smart clothing, exemplified by a smart sports bra, demonstrating how to build responsive, automated factories. His second most cited work (33 citations) introduces a multi-objective instance weighting-based deep transfer learning network, solving the data scarcity problem in industrial fault diagnosis while maintaining high accuracy. Additionally, Lee developed a real-time diagnosis framework (28 citations) for angular misalignment in robot spot-welding systems, using machine learning to monitor voltage and current signals and prevent weld quality degradation. His contributions are vital for advancing Industry 4.0, enabling more efficient, reliable, and automated manufacturing processes. Lee’s research not only pushes the boundaries of intelligent fault diagnosis but also provides practical solutions for real-time monitoring in complex industrial environments.
Research Focus
Key Achievements
Top Papers
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