Yongjae Jeon
Papers
2
Total Citations
7
H-Index
2
About
Yongjae Jeon is a researcher advancing intelligent manufacturing through the integration of robotics and machine learning. His primary focus lies in fault diagnosis for industrial automation, particularly in robotic spot-welding (RSW) processes. Jeon’s most notable contribution is the development of a robust fault diagnosis model that leverages transfer learning to handle variable production situations—a critical innovation for real-world manufacturing environments where conditions constantly shift. This work, published in 2023, has already garnered 5 citations, reflecting its growing relevance in the field. Additionally, Jeon has contributed to the mechanical design of industrial robots, as seen in his dynamic analysis of four-axis palletizing robots, which aids in selecting optimal main components for improved performance and reliability. His research bridges the gap between theoretical modeling and practical deployment, offering solutions that enhance both the intelligence and structural efficiency of automated systems. For students and researchers exploring smart manufacturing, Jeon’s work demonstrates how adaptive algorithms and rigorous mechanical analysis can together drive the next generation of resilient, high-performance robotic applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2Dynamic Analysis to Select Main Parts of Four-Axis Palletizing Robots2 citations · 2020