Papers

2

Total Citations

61

H-Index

2

About

Chao Sun is a researcher specializing in robotics-assisted manufacturing, with a particular focus on precision machining and vibration control in industrial processes. His work centers on the innovative field of robotic assisted milling, a cutting-edge process in which a robotic system supports a workpiece during machine tool cutting operations, enabling significantly improved outcomes for challenging thin-wall component manufacturing. Sun's most influential contribution, "Robotic Assisted Milling for Increased Productivity" (2018), has garnered 49 citations, establishing him as a notable voice in advanced manufacturing research. Building on this foundation, his 2019 paper on form error prediction demonstrates a sophisticated multi-model approach, integrating static force modeling and frequency domain analysis to simulate and minimize geometric inaccuracies during machining — a technically demanding problem with real-world implications for aerospace and precision engineering industries. His research directly addresses the persistent industrial challenge of maintaining dimensional accuracy in flexible, thin-walled workpieces, where vibration and deflection can compromise component quality. By developing predictive and suppressive frameworks for robotic-assisted processes, Sun's work bridges the gap between robotics and traditional machining, offering manufacturers practical pathways to enhanced productivity and product precision.

Research Focus

Key Achievements

2
H-Index
2
Papers
61
Total Citations
31
Avg Citations/Paper
🏆 Most Cited Paper
Robotic assisted milling for increased productivity
49 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Boeing (United Kingdom), University of Sheffield

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago