single-au.php

IJAT Vol.19 No.5 pp. 741-749
doi: 10.20965/ijat.2025.p0741
(2025)

Research Paper:

Tool Path Generation Modified by Predicting Workpiece Deformation Caused by Vise Clamping Using 3D Finite Element Method (FEM)

Koki Kuroda, Hidenori Nakatsuji, and Isamu Nishida ORCID Icon

Graduate School of Engineering, Kobe University
1-1 Rokkodai-cho, Nada-ku, Kobe, Hyogo 657-8501, Japan

Corresponding author

Received:
January 28, 2025
Accepted:
May 22, 2025
Published:
September 5, 2025
Keywords:
tool path generation, computer-aided manufacturing (CAM), finite-element method (FEM), vise, high-precision machining
Abstract

The manufacturing industry faces a labor shortage while needing to achieve high-mix and low-volume production at costs comparable to those of mass production. To enhance flexibility and value in production with limited human resources, increasing labor productivity by reducing production lead time is essential. Automated tool path generation is a promising solution; however, achieving high-precision machining involves not only simply preparing numerical control (NC) programs but also modifying NC programs through test cutting and reviewing machining conditions. One of the factors causing machining errors in cutting is the deformation of the workpiece due to the clamping in the vise. Such deformation can lead to dimensional errors after the workpiece is unclamped, even if it meets tolerances while still on the machine. This study proposes a tool path generation system that considers the deformation of the workpiece caused by the vise, with the purpose of realizing high-precision machining with high efficiency. In this study, a highly compatible computer-aided design model is generated in Standard Triangulated Language format, and the deformation of the workpiece due to clamping is predicted via the finite-element method. The tool path is then generated according to the prediction results to ensure that dimensional tolerances are satisfied after the workpiece is removed from the vise. A case study confirmed that the proposed system can generate numerical control programs that increase the dimensional accuracy of the product.

Cite this article as:
K. Kuroda, H. Nakatsuji, and I. Nishida, “Tool Path Generation Modified by Predicting Workpiece Deformation Caused by Vise Clamping Using 3D Finite Element Method (FEM),” Int. J. Automation Technol., Vol.19 No.5, pp. 741-749, 2025.
Data files:
References
  1. [1] H. Ueno, “Intelligent technologies for machine tools,” Systems, Control and Information, Vol.61, No.3, pp. 107-112, 2017 (in Japanese). https://doi.org/10.11509/isciesci.61.3_107
  2. [2] L. Wang, M. Holm, and G. Adamson, “Embedding a process plan in function blocks for adaptive machining,” CIRP Annals, Vol.59, No.1, pp. 433-436, 2010. https://doi.org/10.1016/j.cirp.2010.03.144
  3. [3] E. Morinaga, T. Hara, H. Joko, H. Wakamatsu, and E. Arai, “Improvement of computational efficiency in flexible computer-aided process planning,” Int. J. Automation Technol., Vol.8, No.3, pp. 396-405, 2014. https://doi.org/10.20965/ijat.2014.p0396
  4. [4] I. Nishida and K. Shirase, “Automatic determination of cutting conditions for NC program generation by reusing machining case data based on geometric properties of removal volume,” J. of Advanced Mechanical Design, Systems, and Manufacturing, Vol.12, No.4, Article No.18-00237, 2018. https://doi.org/10.1299/jamdsm.2018jamdsm0093
  5. [5] Y. Shinoki, M. M. Isnaini, R. Sato, and K. Shirase, “Machining operation planning system which utilize past machining operation data to generate new NC program,” Trans. of the JSME, Vol.81, No.832, Article No.15-00280, 2015 (in Japanese). https://doi.org/10.1299/transjsme.15-00280
  6. [6] Y. Kaneko, H. Tachiya, H. Tamura, H. Shinjo, and M. Isobe, “Simple and effective method to compensate thermal deformation of a machine tool by deriving its approximate equation: Application under the continuous operating condition,” Trans. of the Japan Society of Mechanical Engineers, Series C, Vol.73, No.726, pp. 371-378, 2007 (in Japanese). https://doi.org/10.1299/kikaic.73.371
  7. [7] H. Shi, Y. Xiao, X. Mei, T. Tao, and H. Wang, “Thermal error modeling of machine tool based on dimensional error of machined parts in automatic production line,” ISA Trans., Vol.135, pp. 575-584, 2023. https://doi.org/10.1016/j.isatra.2022.09.043
  8. [8] Y. Hatamura et al., “Development of an intelligent machining center incorporating active compensation for thermal distortion,” CIRP Annals, Vol.42, No.1, pp. 549-552, 1993. https://doi.org/10.1016/S0007-8506(07)62506-2
  9. [9] I. Nishida and K. Shirase, “Machining error correction method based on prediction result of elastic deformation of tool system in endmilling,” Proc. of 2018 JSPE Autumn Conf., pp. 381-382, 2018 (in Japanese). https://doi.org/10.11522/pscjspe.2018A.0_381
  10. [10] V. S. Rao and P. V. M. Rao, “Tool deflection compensation in peripheral milling of curved geometries,” Int. J. of Machine Tools and Manufacture, Vol.46, No.15, pp. 2036-2043, 2006. https://doi.org/10.1016/j.ijmachtools.2006.01.004
  11. [11] B. Denkena, B. Bergmann, and D. Stoppel, “Tool deflection compensation by drive signal-based force reconstruction and process control,” Procedia CIRP, Vol.104, pp. 571-575, 2021. https://doi.org/10.1016/j.procir.2021.11.096
  12. [12] Y. Koike, A. Matsubara, and I. Yamaji, “Design method of material removal process for minimizing workpiece displacement at cutting point,” CIRP Annals, Vol.62, No.1, pp. 419-422, 2013. https://doi.org/10.1016/j.cirp.2013.03.144
  13. [13] J. Wang, S. Ibaraki, and A. Matsubara, “A cutting sequence optimization algorithm to reduce the workpiece deformation in thin-wall machining,” Precision Engineering, Vol.50, pp. 506-514, 2017. https://doi.org/10.1016/j.precisioneng.2017.07.006
  14. [14] R. Ramesh, M. A. Mannan, and A. N. Poo, “Error compensation in machine tools – A review: Part I: Geometric, cutting-force induced and fixture-dependent errors,” Int. J. of Machine Tools and Manufacture, Vol.40, No.9, pp. 1235-1256, 2000. https://doi.org/10.1016/S0890-6955(00)00009-2
  15. [15] K. Teramoto, “On-machine estimation of workpiece deformation for thin-structured parts machining,” Int. J. Automation Technol., Vol.11, No.6, pp. 978-983, 2017. https://doi.org/10.20965/ijat.2017.p0978
  16. [16] J. Zeng, K. Teramoto, and H. Matsumoto, “On-machine estimation of workholding state for thin-walled parts,” Int. J. Automation Technol., Vol.15, No.6, pp. 860-867, 2021. https://doi.org/10.20965/ijat.2021.p0860
  17. [17] K. Kuroda, H. Nakatsuji, and I. Nishida, “Tool path generation in pocket machining considering workpiece deformation using Finite Element Method (FEM),” J. of Advanced Mechanical Design, Systems, and Manufacturing, Vol.18, No.7, Article No.24-00122, 2024. https://doi.org/10.1299/jamdsm.2024jamdsm0089
  18. [18] I. Nishida and K. Shirase, “Automated process planning system for end-milling operation by CAD model in STL format,” Int. J. Automation Technol., Vol.15, No.2, pp. 149-157, 2021. https://doi.org/10.20965/ijat.2021.p0149
  19. [19] A. Kurisaki, “Illustration: The first steps of finite element method for design engineers,” Kodansha Ltd., 2012 (in Japanese).
  20. [20] S. W. Sloan, “A fast algorithm for constructing Delaunay triangulations in the plane,” Advances in Engineering Software, Vol.9, No.1, pp. 34-55, 1987. https://doi.org/10.1016/0141-1195(87)90043-X
  21. [21] T. Taniguchi, “Automatic element segmentation for FEM: Use of delaunay triangulation method,” Morikita Publishing Co., Ltd., 1992 (in Japanese).
  22. [22] T. Taniguchi and K. Moriwaki, “Automatic element segmentation method for 3D FEM,” Morikita Publishing Co., Ltd., 2006 (in Japanese).

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Sep. 05, 2025