Papers
4
Total Citations
16
H-Index
3
About
Xiaoyang Ma is a leading researcher in intelligent robotic welding and additive remanufacturing, with a focus on advancing automation and quality control in manufacturing. Their work centers on developing key technologies for robotic arc additive remanufacturing, automated robotic welding, and real-time defect monitoring. Ma’s major contributions include pioneering multi-source information fusion methods—integrating molten pool and keyhole images with welding parameters—to enable online detection of defects in laser-MAG hybrid welding, achieving high accuracy through a Stacking-PSO-LightGBM model. They also developed a feature-extraction localization algorithm for teaching-free robotic welding using 3D point cloud data, reducing setup time and enhancing flexibility. With over 16 citations across their most-cited papers, Ma’s research has significant impact on improving reliability and efficiency in automated manufacturing. Their 2024 review on robotic arc additive remanufacturing and 2025 review on automated welding technologies serve as essential references for students and researchers, highlighting trends and challenges in the field. Ma’s work is notable for bridging theoretical innovation with practical applications, positioning them as a key contributor to the next generation of smart welding systems.
Research Focus
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Top Papers
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