Yingkang Lu
Papers
2
Total Citations
58
H-Index
2
About
Yingkang Lu is a leading researcher in intelligent manufacturing and production optimization, with a primary focus on human-robot collaboration and assembly line balancing. His work addresses the critical challenge of integrating robotic and human workers in mixed-model two-sided assembly lines—a complex problem central to modern flexible manufacturing. Lu’s major contributions include developing advanced multi-objective optimization algorithms, most notably a discrete artificial bee colony algorithm and a simulated annealing approach, which solve balancing problems under realistic constraints such as setup times and multiple operational limitations. His 2023 paper on human-robot collaborative assembly line balancing has already garnered 34 citations, while his 2024 follow-up study on multi-objective simulated annealing for robotic lines with setup times has earned 24 citations, reflecting the immediate impact and relevance of his research. By enabling efficient and cost-effective deployment of collaborative robots in production systems, Lu’s work bridges the gap between theoretical optimization and practical industrial application, making him a key figure in the evolution of smart manufacturing.
Research Focus
Key Achievements
Top Papers
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