Enyuan Fu
Papers
2
Total Citations
14
H-Index
2
About
Enyuan Fu is a rising scholar in industrial and systems engineering, whose work focuses on the optimization of human-robot collaborative (HRC) assembly systems. Fu’s primary research areas include combinatorial optimization, production line balancing, and the integration of collaborative robots (cobots) into manufacturing environments. Their most notable contribution is the development of an improved combinatorial Benders decomposition algorithm for the human-robot collaborative assembly line balancing problem (HRCALBP). This work, published in 2024, has already garnered 9 citations, reflecting its timely impact on the field. By addressing the complex task of allocating tasks between human workers and cobots to maximize efficiency and safety, Fu’s algorithm provides a powerful tool for designing next-generation flexible assembly lines. The accompanying code and data repository, with 5 citations, further demonstrates Fu’s commitment to open science and reproducible research. As an emerging researcher, Enyuan Fu is helping to shape the future of smart manufacturing, where humans and robots work side by side in optimized, safe, and productive environments.
Research Focus
Key Achievements
Top Papers
- 1
- 2