Kee Jin Park
Papers
1
Total Citations
2
H-Index
1
About
Kee Jin Park is a researcher specializing in precision manufacturing, robotics, and automation, with a particular focus on optimizing mold production processes. His key research areas include off-line programming (OLP) for robotic systems, laser tracking metrology, and automated error analysis in grinding and lapping operations. Park’s major contribution lies in addressing the critical bottleneck of manual finishing in mold manufacturing—a traditionally labor-intensive and error-prone final step that determines mold quality. His work on analyzing automatic teaching position errors using laser trackers has provided a systematic method to enhance the accuracy and efficiency of robotic grinding and lapping systems, reducing reliance on manual operation. While his most-cited paper, "Analysis of Automatic Teaching Position Error to Optimize OLP for Grinding/Lapping Robot System Using Laser Tracker" (2014), has garnered 2 citations, it represents foundational research in bridging the gap between simulation and real-world robotic precision. Park’s efforts have implications for advancing automated mold manufacturing, offering a pathway to improve productivity and quality control in industrial settings. His work is particularly relevant for researchers and engineers seeking to integrate robotics into complex, high-precision manufacturing workflows.
Research Focus
Key Achievements
Top Papers
- 1