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About

Dr. Weihua Fang is a leading researcher in intelligent robotic welding systems, with a primary focus on automated path planning and vision-guided trajectory recognition for complex industrial applications. His work addresses critical challenges in manufacturing precision, particularly for intricate components like open impellers and narrow weld joints. Dr. Fang’s major contributions include developing a novel robot welding path planning and automatic programming method for open impellers (2022, 24 citations), which significantly enhances efficiency and accuracy in production. He also pioneered a vision-based method for narrow weld trajectory recognition (2022, 21 citations), enabling robots to adapt to real-time variations in workpiece geometry. His most recent work introduces a model-based welding trajectory planning approach for identical structural workpieces (2024, 19 citations), further streamlining automation in high-volume manufacturing. With over 60 cumulative citations, Dr. Fang’s research is widely recognized for bridging the gap between theoretical robotics and practical industrial deployment. His achievements have been instrumental in advancing smart manufacturing, reducing human error, and improving weld quality, making him a key contributor to the evolution of autonomous welding systems.