Kyung Min
Papers
1
Total Citations
9
H-Index
1
About
Kyung Min is a leading researcher in the intersection of industrial engineering, human-robot collaboration, and intelligent manufacturing systems. Their work focuses on optimizing complex operational environments where humans and robots work side by side, particularly in logistics and order-picking processes. Min’s most-cited paper, "Agent-based modelling for human–robot collaborative order picking system considering workers’ performance" (2024), has already garnered 9 citations, reflecting its timely relevance. This study introduces a novel agent-based simulation framework that accounts for individual worker performance variability, enabling more realistic and efficient design of collaborative workflows. By integrating behavioral modeling with automation, Min’s research provides actionable insights for improving productivity, safety, and ergonomics in warehouses and factories. Their contributions are particularly valuable as industries increasingly adopt Industry 4.0 and 5.0 paradigms, where human-centric design remains critical. Min’s work has been recognized for bridging theoretical modeling with practical implementation, offering a foundation for future studies on adaptive human-robot teams. With a growing citation record and a focus on real-world impact, Kyung Min is establishing themselves as a key voice in the future of collaborative automation.
Research Focus
Key Achievements
Top Papers
- 1