Dingqi Xue
Papers
1
Total Citations
3
H-Index
1
About
Dingqi Xue is a rising researcher at the forefront of advanced manufacturing, specializing in robotic wire arc additive manufacturing (WAAM) and the integration of deep learning for metallic component fabrication. His work addresses critical challenges in producing medium- to large-scale metal parts, combining high deposition efficiency with cost-effectiveness. Xue’s most notable contribution is his 2024 paper, "Deep learning assisted fabrication of metallic components using the robotic wire arc additive manufacturing," which has already garnered 3 citations—a strong early indicator of its impact in a rapidly evolving field. This study pioneers the use of artificial intelligence to optimize WAAM processes, enhancing precision and reducing defects in real-time. By bridging machine learning with robotic fabrication, Xue is helping to transform additive manufacturing from a prototyping tool into a viable production method for industries like aerospace and automotive. His research stands out for its practical focus on improving manufacturing reliability and scalability, making him a promising voice in the next generation of manufacturing engineers.
Research Focus
Key Achievements
Top Papers
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