Zilei Wen
Papers
2
Total Citations
6
H-Index
2
About
Zilei Wen is a researcher at the forefront of advanced manufacturing, specializing in high-speed robotic milling and precision machining. His work addresses a critical challenge in modern industry: enabling industrial robots, which are inherently less rigid than traditional machine tools, to perform high-precision milling tasks. Wen’s major contributions center on real-time process monitoring and quality control. His most cited work, "Online Vibration Detection in High-Speed Robotic Milling Process Based on Wavelet Energy Entropy of Acoustic Emission" (2024, 4 citations), introduces a novel method using acoustic emission signals to detect harmful vibrations during cutting, a key step toward stable, automated robotic machining. Complementing this, his study on "Surface morphology, burr formation, and spindle axial drift" (2024, 2 citations) systematically investigates how cutting parameters affect surface quality and tool stability when milling complex features. By tackling the fundamental limitations of robot stiffness and instability, Wen’s research is paving the way for more flexible, cost-effective manufacturing solutions. His work is particularly notable for its direct industrial relevance, offering practical insights for deploying robots in high-precision metal cutting applications.
Research Focus
Key Achievements
Top Papers
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- 2