Min-Woo Na

Korea University

Papers

1

Total Citations

40

H-Index

1

About

Min-Woo Na is a researcher specializing in intelligent manufacturing and assembly process monitoring, with a focus on integrating sensor data for real-time quality control. His most cited work, "Assembly process monitoring algorithm using force data and deformation data" (2018, 40 citations), introduces a novel approach that combines force and deformation measurements to detect anomalies during assembly operations. This contribution is significant for advancing smart manufacturing systems, enabling more reliable and adaptive production lines. Na’s research bridges mechanical engineering and data-driven algorithms, offering practical solutions for industry 4.0 applications. With 40 citations, this paper demonstrates his impact in the field, particularly among researchers working on process monitoring and fault detection. His work is notable for its emphasis on real-time data fusion, which enhances the precision and efficiency of assembly processes. Na’s achievements contribute to the broader goal of automating quality assurance in manufacturing, making his research valuable for both academic and industrial audiences.

Research Focus

Key Achievements

1
H-Index
1
Papers
40
Total Citations
40
Avg Citations/Paper
🏆 Most Cited Paper
Assembly process monitoring algorithm using force data and deformation data
40 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Korea University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago