Papers
53
Total Citations
3,126
H-Index
26
About
Zengxi Pan is a prominent researcher whose work spans advanced manufacturing, robotics, and process automation, with particular expertise in wire and arc additive manufacturing (WAAM) and robotic machining. His foundational 2014 paper introducing a multi-bead overlapping model for WAAM has accumulated over 547 citations, establishing him as a leading authority in metal additive manufacturing and shaping how researchers approach robotic deposition processes. Alongside this, his investigations into robotic machining performance—tackling the critical challenge of chatter vibration caused by industrial robots' comparatively low stiffness—have drawn over 350 citations, with follow-on work exploring both regenerative and mode coupling chatter mechanisms and innovative suppression strategies using magnetorheological elastomer absorbers. Pan has also made significant contributions to robot programming methodologies and motion capture technologies for robotic systems, reflecting a broad systems-level perspective. More recently, he has advanced intelligent process monitoring in WAAM through deep learning-based melt pool vision systems and model predictive control of layer geometry, demonstrating a sustained commitment to closing the loop between manufacturing process and automation. Collectively, his body of work—exceeding 1,800 citations across his most impactful papers—has meaningfully advanced the reliability and intelligence of modern robotic manufacturing systems.
Research Focus
Key Achievements
Top Papers
- 1
- 2Chatter analysis of robotic machining process351 citations · 2006
- 3Recent progress on programming methods for industrial robots263 citations · 2011
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- 8Model predictive control of layer width in wire arc additive manufacturing110 citations · 2020
- 9
- 10Motion capture in robotics review89 citations · 2009