Jong Pyo Lee
Papers
2
Total Citations
7
H-Index
2
About
Jong Pyo Lee is a researcher specializing in robotic arc welding, seam tracking technology, and intelligent manufacturing systems. His work focuses on improving the precision and reliability of Gas Metal Arc (GMA) welding processes through advanced computational methods. Lee’s major contributions include developing the Mahalanobis Distance Method for assessing welding quality in robotic systems, which enhances defect detection and process optimization. He has also pioneered image processing algorithms for laser vision-based seam tracking, enabling cost-effective, real-time adjustments during welding operations. His most-cited papers—"A Study on Welding Quality of Robotic Arc Welding Process Using Mahalanobis Distance Method" (2013, 4 citations) and "A Study on Image Processing Algorithms for Seam Tracking System in GMA Welding" (2015, 3 citations)—demonstrate his impact in advancing automation and quality control in manufacturing. Lee’s research bridges theoretical algorithms with practical industrial applications, offering scalable solutions for robotic welding challenges. His work is particularly valuable for students and researchers exploring smart manufacturing, sensor integration, and process optimization in arc welding.
Research Focus
Key Achievements
Top Papers
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