Zhibing Liu
Papers
4
Total Citations
67
H-Index
3
About
Zhibing Liu is a leading researcher in the field of robotic machining, specializing in the dynamics, stability, and precision of robotic milling systems. His work directly addresses the critical challenge of chatter—a self-excited vibration that degrades surface quality and limits productivity in industrial robotics. Liu’s major contributions include the development of an updated full-discretization method for predicting chatter stability under varying cutter orientations, a technique that has become essential for process parameter selection. He has also pioneered early chatter identification using optimized variational mode decomposition (VMD) with multi-band information fusion, enabling real-time, sensitive detection of instability. His research further explores dynamic modeling that accounts for force-induced deformation and its effect on regenerative chatter and process damping, providing a more accurate stability prediction framework. With his most-cited paper garnering 37 citations and several recent works accumulating over 65 citations, Liu’s impact is rapidly growing. His latest work on dynamic posture programming for robotic milling, based on cutting force directional stiffness performance, promises to enhance the machining of large aerospace components. Liu’s research is pivotal for advancing the reliability and efficiency of robotic manufacturing.
Research Focus
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Top Papers
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