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IJAT Vol.8 No.3 pp. 437-444
doi: 10.20965/ijat.2014.p0437
(2014)

Paper:

Using a Four-Dimensional Mesh Model to Represent a Tool Motion Trajectory in Five-Axis Machining

Hirotaka Kameyama*,**, Ikuru Otomo*, Masahiko Onosato*,
and Fumiki Tanaka*

*Hokkaido University, N14W9, Kita-ku, Sapporo 060-0814, Japan

**Currently, Toshiba Co. Ltd.

Received:
December 1, 2013
Accepted:
April 14, 2014
Published:
May 5, 2014
Keywords:
four-dimensional mesh model, spatiotemporal model, workpiece transformation, five-axis machining
Abstract

In the field of machining processes, three-Dimensional (3D) models are commonly used to simulate the motions of cutting tools and workpieces. However, it is difficult for 3D models to represent spatio-temporal changes in their shapes continuously and to a high degree of accuracy. The objective of this study is to represent the 5-axis cutting process of workpiece transformation explicitly using a spatio-temporal model, the “four-Dimensional (4D) mesh model.” Every 4D mesh model is defined with bounding tetrahedral cells, and can continuously represent spatio-temporal changes of shape, position and orientation. In this study, the five-axis cutting process is described using accumulated volumes of 4D mesh models. Accumulated volumes are total volumes determined by spaces through which the object has passed. The use of accumulated volumes enables us to record tool-swept volumes and material removal shapes. First, this report introduces a 4D mesh model and the development of a 4D mesh modeling system. Next, a method of representing accumulated volumes as 4D mesh models is proposed. Generated 4D models are observed as 3D models by means of cross-section extraction.

Cite this article as:
H. Kameyama, I. Otomo, M. Onosato, and <. Tanaka, “Using a Four-Dimensional Mesh Model to Represent a Tool Motion Trajectory in Five-Axis Machining,” Int. J. Automation Technol., Vol.8, No.3, pp. 437-444, 2014.
Data files:
References
  1. [1] K. Morishige, S. Ishizuka, and Y. Takeuchi, “Development of Tool Fabrication CAD/CAM for Conicoid End Mill,” Int. J. of Automation Technology, Vol.1, No.2, pp. 128-135, 2007.
  2. [2] A. Matsubara and S. Ibaraki, “Monitoring and Control of Cutting Forces in Machining Processes: A Review,” Int. J. of Automation Technology, Vol.3, No.4, pp. 445-456, 2009.
  3. [3] E. Morinaga, M. Yamada, H. Wakamatsu, and E. Arai, “Flexible Process Planning Method for Milling,” Int. J. of Automation Technology, Vol.5, No.5, pp. 700-707, 2011.
  4. [4] H. Iwabe, et al., “Study on Performance of Radius End Milling Titanium Alloy (Analysis of Cutting Cross-Sectional Area Using 3DCAD and Experiments of Inclined Surface with Contouring),” Int. J. of Automation Technology, Vol.7, No.3, pp. 270-277, 2013.
  5. [5] D. Jang, K. Kim, and J. Jung, “Voxel-Based Virtual Multi-Axis Machining,” Advanced Manufacturing Technology, Vol.16, No.10, pp. 709-713, 2000.
  6. [6] Z. Shao, R. Guo, J. Li, and J. Peng, “Accurate Modeling Method for Generalized Tool Swept Volume in 5-axis NC Machining Simulation,” J. of Software, Vol.6, No.10, pp. 2056-2063, Oct. 2011.
  7. [7] K. Nakamoto, T. Inaoka, K. Shirase, and T. Moriwaki, “Development of a Process Planning System for 5-axis Controlled MachineTool (1st Report): Determination of Tool Posture by Estimating Removal Volume and Cutting Time Based on Voxel Model,” J. of the Japan Society for Precision Engineering, Vol.73, No.9, 2007.
  8. [8] K. Shirase, K. Nakamoto, E. Arai, and T. Moriwaki, “Real-Time Five-Axis Control Based on Digital Copy Milling Concept to Achieve Autonomous Milling,” Int. J. of Automation Technology, Vol.2, No.6, pp. 418-424, 2008.
  9. [9] K. Shirase and K. Nakamoto, “Simulation Technologies for the Development of an Autonomous and Intelligent Machine Tool,” Int. J. of Automation Technology, Vol.7, No.1, pp. 6-15, 2013.
  10. [10] J. Kaneko, K. Teramoto, M. Onosato, and Y. Takeuchi, “Cutting Force Prediction on the Basic of Actual Depth of Cut in End Milling,” Proc. of Int. Conf. on Leading EdgeManufacturing in 21st Century (LEM21), Niigata, pp. 777-782, 2003.
  11. [11] T. atsumura, T. Shirakashi, and E. Usui, “Adaptive Cutting Force Prediction in Milling Processes,” Int. J. of Automation Technology, Vol.4, No.3, pp. 221-228, 2010.
  12. [12] T. Matsumura, M. Shimada, K. Teramoto, and E. Usui, “Predictive Cutting Force Model and Cutting Force Chart for Milling with Cutter Axis Inclination,” Int. J. of Automation Technology, Vol.7, No.1, pp. 30-38, 2013.
  13. [13] H. Narita, “A Determination Method of Cutting Coefficients in Ball End Milling Forces Model,” Int. J. of Automation Technology, Vol.7, No.1, pp. 39-44, 2013.
  14. [14] M. Onosato, R. Kawagishi, K. Kato, H. Date, and F. Tanaka, “Fourdimensional MeshModeling for Spatio-Temporal Object Representation,” Proc. of Asian Conf. on Design and Digital Engineering 2010 (ACDDE 2010), pp. 579-589, Jeju, Korea, 2010.
  15. [15] S. Cameron, “Collision Detection by Four-Dimensional Intersection Testing,” IEEE Trans. on Robotics and Automation, Vol.6, No.3, pp. 291-302, 1990.
  16. [16] J. P. Zhang and Z. Z. Hu, “BIM- and 4D-based integrated solution of analysis and management for conflicts and structural safety problems during construction: 1. Principles and methodologies,” Automation in Construction, No.20, pp. 155-160, 2011.
  17. [17] K. M. Brock, et al., “Automated generation of a four-dimensional model of the liver using warping and mutual information,” Medical Physics, Vol.30, No.6, pp. 1128-1133, 2003.
  18. [18] E. Aganj, J-P. Pons, and R. Keriven, “Globally optimal spatiotemporal reconstruction from cluttered videos,” Proc. 9th Asian Conf. on Computer Vision, pp. 667-678, 2009.
  19. [19] E. Eisemann, et al., “Single-Pass GPU Solid Voxelization for Real-Time Application,” Proc. Graphics Interface 2008, pp. 73-80, 2008.
  20. [20] P. Bhaniramka, R. Wenger, and R. Crawfis, “Isosurfacing in higher dimensions,” Proc. of the conf. on Visualization ���00, 267-273, 2000.
  21. [21] W. E. Lorensen and H. E. Cline, “Marching cubes: A high resolution 3d surface construction algorithm,” Computer Graphics, Vol.21, No.4, pp. 163-169, 1987.
  22. [22] J. R. Shewchuk, “Constrained Delaunay Tetrahedralizations and Provably Good Boundary Recovery,” Proc. of 11th Int. Meshing Roundtable, Sandia National Laboratories, pp. 193-204, 2002.
  23. [23] I. Otomo, M. Onosato, and F. Tanaka, “Direct Construction of a Four-Dimensional Mesh Model from Three-Dimensional Object with Continuous Rigid Body Movement,” J. of Computational Design and Engineering, Vol.1, No.2, pp. 96-102, 2014.

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