Hengjian Feng

About

Hengjian Feng is a leading researcher in advanced robotic manufacturing, with a primary focus on robotic belt grinding and precision surface processing. His work centers on developing intelligent, data-driven methods to enhance the efficiency and accuracy of material removal for complex geometries, particularly in the aerospace and superalloy sectors. Feng’s major contributions include a novel material removal rate model based on single grain force (71 citations), which provides a fundamental understanding of grinding mechanics, and innovative point cloud-based techniques for 3D parent surface reconstruction and weld seam feature extraction (56 citations). He has also pioneered a feature-guided trajectory generation method for robotic grinding of freeform welds (41 citations), enabling automated path planning from raw sensor data. His comprehensive review of recent advances in robotic belt grinding of superalloys (29 citations) synthesizes key technological trends. With over 197 citations across his top papers, Feng’s work bridges theoretical modeling and practical automation, offering critical insights for students and researchers in manufacturing robotics, surface engineering, and intelligent machining systems.

Research Focus

Key Achievements

Top Papers

1. 1
   A novel material removal rate model based on single grain force for robotic belt grinding

   71 citations · 2021
2. 2
   Point cloud 3D parent surface reconstruction and weld seam feature extraction for robotic grinding path planning

   56 citations · 2020
3. 3
   A novel feature-guided trajectory generation method based on point cloud for robotic grinding of freeform welds

   41 citations · 2021
4. 4
   A review of recent advances in robotic belt grinding of superalloys

   29 citations · 2023

Key Collaborators

Contact & Links