Jingwei Tang
Papers
1
Total Citations
11
H-Index
1
About
Jingwei Tang is a leading researcher in intelligent manufacturing and human-robot collaboration, with a focus on dynamic task allocation and digital twin technologies. Their most-cited work, "A dynamic task allocation framework for human-robot collaborative assembly based on digital twin and IGA-TS" (2025, 11 citations), introduces a novel framework that integrates digital twins with an improved genetic algorithm and tabu search (IGA-TS) to optimize real-time task distribution between humans and robots in assembly environments. This contribution addresses critical challenges in adaptive manufacturing, enabling safer and more efficient collaboration by leveraging real-time data and predictive modeling. Tang’s research has significant implications for Industry 4.0, particularly in enhancing flexibility and productivity in smart factories. With growing recognition in the field, their work is paving the way for more responsive and intelligent production systems, making Tang a notable figure in advancing human-robot interaction and digital twin applications.
Research Focus
Key Achievements
Top Papers
- 1