Xinpeng Zu
Papers
2
Total Citations
14
H-Index
2
About
Xinpeng Zu is a researcher at the forefront of advanced manufacturing and precision engineering, with a primary focus on abrasive tool condition monitoring and robotic belt grinding processes. His work addresses critical challenges in material removal mechanisms and tool wear prediction, particularly for high-performance alloys used in aerospace applications. Zu’s most cited paper, "The accuracy losing phenomenon in abrasive tool condition monitoring and a novel WMMC-JDA based data-driven method considered tool stochastic surface morphology" (2023, 11 citations), introduces an innovative data-driven approach that accounts for the stochastic nature of tool surfaces, significantly improving monitoring accuracy. His subsequent work, "Theoretical investigation of anisotropic material removal mechanism in robotic belt grinding single crystal superalloy process" (2024, 3 citations), delves into the complex anisotropic behavior of superalloys, providing foundational insights for optimizing robotic grinding strategies. Though early in his career, Zu’s contributions are already shaping the future of intelligent manufacturing, bridging theoretical mechanics with practical, data-driven solutions. His research holds promise for enhancing efficiency and precision in critical industries like aerospace and automotive manufacturing.
Research Focus
Key Achievements
Top Papers
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