Ningjian Huang

General Motors (United States)

Papers

3

Total Citations

61

H-Index

3

About

Ningjian Huang is a researcher specializing in human-robot collaboration, manufacturing systems engineering, and ergonomic performance optimization. His work sits at the critical intersection of industrial productivity and worker well-being, addressing one of modern manufacturing's most pressing challenges: how to effectively integrate collaborative robots alongside human operators. Huang's most significant contributions focus on developing rigorous analytical frameworks for evaluating human-robot collaborative assembly systems. His landmark 2021 paper introducing an integrated model of productivity and ergonomic performance (34 citations) filled a notable gap in the literature by simultaneously analyzing both dimensions—previously treated in isolation. Complementing this, his systems-approach analysis of assembly-time performance (21 citations) provides manufacturers with practical tools for reducing station processing times through strategic robot deployment. His third notable work extends this analytical tradition by examining flow time dynamics in collaborative assembly processes, offering system property insights valuable for real-world implementation. Collectively published in 2021, these papers signal a productive and focused research agenda that has already garnered over 60 citations, demonstrating meaningful uptake within the manufacturing engineering community. Huang's research offers particularly valuable guidance for organizations navigating the transition from traditional manual operations to intelligent, human-centered automated production environments.

Research Focus

Key Achievements

3
H-Index
3
Papers
61
Total Citations
20
Avg Citations/Paper
🏆 Most Cited Paper
From Manual Operation to Collaborative Robot Assembly: An Integrated Model of Productivity and Ergonomic Performance
34 citations · 2021
📈 Most Prolific Year: 2021 (3 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: General Motors (United States)

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago