Chan-Hee Won

Korea Institute of Industrial Technology

Papers

Total Citations

H-Index

About

Chan-Hee Won is a leading researcher in intelligent manufacturing and welding process monitoring, with a focus on real-time quality assessment through advanced sensor fusion and machine learning. 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 bottleneck in automated welding: the lack of objective, timely, and cost-effective evaluation methods. By integrating infrared thermal imaging with machine vision and artificial neural networks, Won pioneered a non-invasive approach to predict internal weld penetration in real time—a breakthrough that moves beyond traditional, post-process inspection. This work exemplifies his broader contributions to cyber-physical production systems, where sensor-driven data and AI models replace subjective human judgment. Won’s research has significant implications for industries relying on robotic welding, offering enhanced reliability and efficiency. With growing citation impact, his innovations are shaping the next generation of smart manufacturing, positioning him as a key figure in the transition toward fully autonomous quality control in welding processes.