Efficient numerical-control simulation for multi-axis machining based on three-level grids

doi:10.1007/s40436-024-00539-4

Advances in Manufacturing ›› 2025, Vol. 13 ›› Issue (4): 718-736.doi: 10.1007/s40436-024-00539-4

• • 上一篇

Efficient numerical-control simulation for multi-axis machining based on three-level grids

Zheng-Wen Nie¹, Jia-Bin Cao¹, Yi-Yang Zhao¹, Lin Zhang¹, Xun Liu¹, Yan Xu², Yan-Zheng Zhao¹

1. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China;
2. College of Computer and Control Engineering, Northeast Forestry University, Harbin, 150036, People's Republic of China

收稿日期:2024-04-01 修回日期:2024-05-22 发布日期:2025-12-06
通讯作者: Yan-Zheng Zhao Email:E-mail:yzh-zhao@sjtu.edu.cn E-mail:yzh-zhao@sjtu.edu.cn
作者简介:Zheng-Wen Nie received the B.Sc. in Industrial Design from Northeastern University and MA.Sc. in Mechanical Engineering from Hong Kong Polytechnic University. He received his Ph.D in Mechanical Engineering from University of British Columbia, under the supervision of Professor Hsi-Yung Feng. He worked as a postdoctoral fellow for Professor Yusuf Altintas. He is currently working in School of Mechanical Engineering, Shanghai Jiao Tong University. His research interests include computer aided manufacturing, virtual machining, collision detection.
Jia-Bin Cao received the B.Sc. in Automation from Harbin Engineering University. He is currently a postgraduate in School of Mechanical Engineering, Shanghai Jiao Tong University. His main research interests are robotic machining, vibration control, intelligent control.
Yi-Yang Zhao received his B.S. degrees in Automatic from Harbin Institute of Technology, Harbin, China in 2014 and the Ph.D. degree in Mechanical Engineering from Shanghai Jiao Tong University, Shanghai, China in 2024. His research is mainly in the area of harmonic reducer performance, industrial robot calibration and compression, high precision and stiffness robot for milling.
Lin Zhang is an associate professor from Yantze Normal University. He received a B.Sc. in Mechanical Engineering and Automation and a Ph.D. in Mechanical Manufacturing and Automation from China University of Mining and Technology. He received a joint Ph.D. at University of California San Diego. He is currently working in School of Mechanical Engineering, Shanghai Jiao Tong University as a postdoc. His main research interests are climbing robotics, intelligent control, metamorphotic theory, sensorless sensing, and reinforcement robot learning.
Xun Liu received the Ph.D. degree from the College of Computer and Control Engineering, Northeast Forestry University. He is a Postdoc in Mechanical Engineering with Shanghai Jiao Tong University, Shanghai, China. His research interests include robot control, motion planning and control algorithm.
Yan Xu received the master’s degree in Mechanical Engineering from Northeastern University, Liaoning province, China, in 2020. She is currently pursuing the PhD degree in the College of Computer and Control Engineering, Northeast Forestry University. Her current research focuses on robot motion planning, high-precision trajectory planning, and composite robot control.
Yan-Zheng Zhao was born in 1965. He graduated from Harbin Institute of Technology with a master degree in hydraulics and pneumatics. He worked at the Institute of Robotics of Harbin Institute of Technology. In 1995, he went to study in the Faculty of Engineering of Miyazaki University in Japan for one year and was promoted to professor in 2000. His main research interests are in the design, manufacture and control of special robots.
基金资助:
This study was supported by the National Key Research and Development Program for Robotics Serialized Harmonic Reducer Fatigue Performance Analysis and Prediction and Life Enhancement Technology Research (Grant No. 2017YFB1300603).

Efficient numerical-control simulation for multi-axis machining based on three-level grids

Zheng-Wen Nie¹, Jia-Bin Cao¹, Yi-Yang Zhao¹, Lin Zhang¹, Xun Liu¹, Yan Xu², Yan-Zheng Zhao¹

1. School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, People's Republic of China;
2. College of Computer and Control Engineering, Northeast Forestry University, Harbin, 150036, People's Republic of China

Received:2024-04-01 Revised:2024-05-22 Published:2025-12-06
Contact: Yan-Zheng Zhao Email:E-mail:yzh-zhao@sjtu.edu.cn E-mail:yzh-zhao@sjtu.edu.cn
Supported by:
This study was supported by the National Key Research and Development Program for Robotics Serialized Harmonic Reducer Fatigue Performance Analysis and Prediction and Life Enhancement Technology Research (Grant No. 2017YFB1300603).

摘要/Abstract

摘要： This paper presents an accurate and efficient method for computing machined part geometry and determining cutter-workpiece engagement (CWE) in multi-axis milling. The proposed method is based on volumetric models, with three types of three-level data structures proposed to represent a solid workpiece voxel model for a sparse and memory-efficient implementation. At each cutter location, every coarse workpiece voxel is efficiently updated from the top to the lower level, and the vertex states and edge intersection points inside each bottom-level voxel crossed by the cutter envelope surface continue to be updated using the dynamic marching cube algorithm. Meanwhile, the finest intersecting voxels are projected onto the cutter surface such that the projected engagement patches connect to form the required engagement map. Finally, according to the lookup table, a triangular mesh of the machined part is built by reconstructing and fusing the approximation polygons inside the bottom-level workpiece surface voxels. Quantitative comparisons of the proposed method against the two-level grid and the tri-dexel model demonstrated the high accuracy and considerable ability of the proposed method to provide more significant and stable efficiency improvement without being affected by a large branching factor owing to its more efficient spatial partitioning.

The full text can be downloaded at https://doi.org/10.1007/s40436-024-00539-4

关键词: Machining simulation, Voxel, Three-level grid, Workpiece update, Cutter-workpiece engagement (CWE)

Abstract: This paper presents an accurate and efficient method for computing machined part geometry and determining cutter-workpiece engagement (CWE) in multi-axis milling. The proposed method is based on volumetric models, with three types of three-level data structures proposed to represent a solid workpiece voxel model for a sparse and memory-efficient implementation. At each cutter location, every coarse workpiece voxel is efficiently updated from the top to the lower level, and the vertex states and edge intersection points inside each bottom-level voxel crossed by the cutter envelope surface continue to be updated using the dynamic marching cube algorithm. Meanwhile, the finest intersecting voxels are projected onto the cutter surface such that the projected engagement patches connect to form the required engagement map. Finally, according to the lookup table, a triangular mesh of the machined part is built by reconstructing and fusing the approximation polygons inside the bottom-level workpiece surface voxels. Quantitative comparisons of the proposed method against the two-level grid and the tri-dexel model demonstrated the high accuracy and considerable ability of the proposed method to provide more significant and stable efficiency improvement without being affected by a large branching factor owing to its more efficient spatial partitioning.

The full text can be downloaded at https://doi.org/10.1007/s40436-024-00539-4

Key words: Machining simulation, Voxel, Three-level grid, Workpiece update, Cutter-workpiece engagement (CWE)

Zheng-Wen Nie, Jia-Bin Cao, Yi-Yang Zhao, Lin Zhang, Xun Liu, Yan Xu, Yan-Zheng Zhao. Efficient numerical-control simulation for multi-axis machining based on three-level grids[J]. Advances in Manufacturing, 2025, 13(4): 718-736.

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Efficient numerical-control simulation for multi-axis machining based on three-level grids

Efficient numerical-control simulation for multi-axis machining based on three-level grids

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