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About

Chunyang Xia is a leading researcher in advanced manufacturing, specializing in wire arc additive manufacturing (WAAM), welding process monitoring, and intelligent quality control. His work bridges the gap between traditional manufacturing and cutting-edge artificial intelligence, with a focus on real-time process optimization. Xia’s most impactful contribution is his pioneering use of model predictive control to regulate layer width in WAAM, a breakthrough that enhances precision and repeatability in 3D metal printing—his 2020 paper on this topic has garnered 110 citations. He further advanced the field by developing a deep learning-based vision system for melt pool monitoring (102 citations), enabling autonomous defect detection during deposition. His recent work tackles the complexity of laser-MAG hybrid welding by fusing multi-source sensor data—including molten pool and keyhole images—with a Stacking-PSO-LightGBM model to detect defects with unprecedented reliability, as outlined in his 2025 study. Xia’s research is distinguished by its practical impact, offering scalable solutions for industrial automation. His integration of computer vision and machine learning into additive and welding processes positions him as a key innovator in smart manufacturing, with his methods directly improving production quality and reducing waste in real-world applications.