Papers

6

Total Citations

80

H-Index

5

About

Yue Zang is a leading researcher at the intersection of intelligent manufacturing and sustainable robotics, with a primary focus on automated disassembly systems for electric vehicle (EV) batteries. Their work addresses a critical bottleneck in the circular economy: the safe, efficient, and scalable disassembly of end-of-life EV batteries. Zang has pioneered the use of vision systems and fuzzy logic for quality estimation in resistance spot welding, achieving 25 citations for this foundational work. More recently, they have become a key voice in robotic disassembly, with their 2024 paper on technologies and opportunities for EV battery disassembly garnering 24 citations and highlighting the pressing need for smart automation. Zang’s research also tackles fundamental challenges in robotic manipulation, including jamming problems in dual peg-hole disassembly and skill acquisition through reinforcement learning augmented with external knowledge. With a growing portfolio of highly cited papers, Zang is shaping the future of remanufacturing by enabling robots to handle the uncertainty and complexity of real-world disassembly tasks, directly supporting the transition to a more sustainable automotive industry.

Research Focus

Key Achievements

5
H-Index
6
Papers
80
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
A Novel Method of Using Vision System and Fuzzy Logic for Quality Estimation of Resistance Spot Welding
25 citations · 2019
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 17
🏛 Institutions: Wuhan University of Technology, University of Birmingham

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago