Xiaoqing Jiang

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About

Dr. Xiaoqing Jiang is at the forefront of advancing robotic friction stir welding (RFSW), a critical technology for modern manufacturing. His research focuses on overcoming the inherent limitations of serial industrial robots—specifically their low stiffness, which causes significant end-effector deviations and vibrations under welding forces. Dr. Jiang’s major contributions include pioneering a digital twin virtual welding approach that integrates co-simulation of finite element analysis (FEA) and robotic models. This innovation allows for precise prediction and compensation of robotic deformations, enhancing weld quality and process reliability. Additionally, he developed a dynamic dual particle swarm optimization method to optimize the installation position of complex space curve weldments, further improving accuracy and reducing operational errors. His most-cited work (2024) has already garnered 19 citations, underscoring its immediate impact on the field. By bridging simulation and real-world application, Dr. Jiang’s research not only advances the theoretical understanding of RFSW but also provides practical solutions for industrial automation. His achievements are instrumental in making friction stir welding more adaptable and precise, paving the way for its broader adoption in aerospace, automotive, and other high-stakes industries.