Papers
1
Total Citations
73
H-Index
1
About
Dr. Jingwei Li is a leading researcher in intelligent manufacturing and robotic path optimization, with a particular focus on welding automation. Their most influential work, "Research on Intelligent Welding Robot Path Optimization Based on GA and PSO Algorithms" (2018, 73 citations), introduces a groundbreaking approach to enhancing industrial productivity. By developing and comparing genetic algorithm (GA) and discrete particle swarm optimization (PSO) techniques, Dr. Li demonstrated how intelligent algorithms can significantly improve welding robot path efficiency, reducing operational costs and production time. This research has become a cornerstone reference for engineers and academics working on robotic motion planning and swarm intelligence applications in manufacturing. Dr. Li's contributions bridge the gap between theoretical optimization methods and practical industrial implementation, offering scalable solutions for complex welding tasks. Their work is widely cited in studies on evolutionary computation, industrial robotics, and smart factory automation, reflecting its lasting impact on both research and real-world manufacturing systems.
Research Focus
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Top Papers
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