single-au.php

IJAT Vol.19 No.6 pp. 1076-1085
doi: 10.20965/ijat.2025.p1076
(2025)

Research Paper:

High-Precision Machining with Positioning Control Considering Structural Deformation of Small Machine-Tool

Yusuke Ueno*,† and Hiroshi Tachiya** ORCID Icon

*Faculty of Production Systems Engineering and Sciences, Komatsu University
1-3 Nu, Shicho-machi, Komatsu, Ishikawa 923-8511, Japan

Corresponding author

**Advanced Mobility Research Institute, Kanazawa University
Kanazawa, Japan

Received:
April 9, 2025
Accepted:
August 12, 2025
Published:
November 5, 2025
Keywords:
small machine tool, deformation, machine error compensation, strain measurement
Abstract

The size of general-purpose machine tools used in production tends to be oversized for the parts being produced. Downsizing these machine tools can reduce manufacturing costs by decreasing the size of large production lines. Additionally, smaller machine tools can be easily transported and installed, facilitating the construction of flexible production lines that can adapt to changes in demand. However, downsizing machine tools reduces structural rigidity, leading to deformation due to cutting forces. The displacement of the tool from the target position caused by this deformation makes high-precision machining of hard materials, such as steel, difficult. This study proposes a method to reduce machining errors in small machine tools by predicting deformation during cutting and compensating for tool position based on the results of a simple static load test. To verify the effectiveness of the proposed method, a new small 3-axis NC milling machine was developed. The proposed method successfully reduced machining errors by 87% in the side cutting of a steel workpiece.

Cite this article as:
Y. Ueno and H. Tachiya, “High-Precision Machining with Positioning Control Considering Structural Deformation of Small Machine-Tool,” Int. J. Automation Technol., Vol.19 No.6, pp. 1076-1085, 2025.
Data files:
References
  1. [1] Y. Okazaki, “Micro factory,” J. of the Japan Society of Precision Engineering, Vol.68, No.4, pp. 491-494, 2002 (in Japanese). https://doi.org/10.2493/jjspe.68.491
  2. [2] H. Ohmori and Y. Uehara, “Development of a desktop machine tool for mirror surface grinding,” Int. J. Automation Technol., Vol.4, No.2, pp. 88-96, 2010. https://doi.org/10.20965/ijat.2010.p0088
  3. [3] Y. Kuroda, ““MONOZUKURI” innovation technologies supporting parts and factory evolution,” Denso Technical Review, Vol.20, pp. 26-34, 2015 (in Japanese).
  4. [4] K. Ashida, S. Nakano, J. Park, and J. Akedo, “On-demand MEMS device production system by Module-based microfactory,” Int. J. Automation Technol., Vol.4, No.2, pp. 110-116, 2010. https://doi.org/10.20965/ijat.2010.p0110
  5. [5] N. Suzuki, Y. Morimoto, Y. Kaneko, K. Hirosaki, and Y. Okazaki, “Development of miniaturized machine tool with pipe frame structure,” J. of the Japan Society for Precision Engineering, Vol.86, No.2, pp. 130-135, 2020 (in Japanese). https://doi.org/10.2493/jjspe.86.130
  6. [6] T. Ogawa, “Building of efficient, energy-saving lines with an extremely-compact machining center and CNC lathe,” Int. J. Automation Technol., Vol.4, No.2, pp. 150-154, 2010. https://doi.org/10.20965/ijat.2010.p0150
  7. [7] Compact Line Revolution, Nikkei Inc., 2013 (in Japanese).
  8. [8] H. Kato, K. Shintani, and K. Iwata, “High-speed milling using a developed desktop machine tool,” Int. J. Automation Technol., Vol.4, No.2, pp. 103-109, 2010. https://doi.org/10.20965/ijat.2010.p0103
  9. [9] K. Sugito, “1/N machine system for the lean factory,” Int. J. Automation Technol., Vol.11, No.4, pp. 623-628, 2017. https://doi.org/10.20965/ijat.2017.p0623
  10. [10] C. Endo, “Small processing machinery effectiveness in micropart processing and factory construction with desktop production equipment,” Int. J. Automation Technol., Vol.4, No.2, pp. 155-159, 2010. https://doi.org/10.20965/ijat.2010.p0155
  11. [11] S. Shimizu, “Machine tool design studies (basic),” Japan Machine Tool Builders Association, 1998 (in Japanese).
  12. [12] Y. Kijima, “Design and development of miniature manufacturing systems,” J. of the Japan Society for Precision Engineering, Vol.77, No.3, pp. 269-272, 2011 (in Japanese). https://doi.org/10.2493/jjspe.77.269
  13. [13] S. Yoshimitsu, D. Iwashita, K. Shimana, Y. Kobaru, and S. Yamashita, “Monitoring of cutting state in end-milling based on measurement of tool behavior using CCD image,” Int. J. Automation Technol., Vol.13, No.1, pp. 133-140, 2019. https://doi.org/10.20965/ijat.2019.p0133
  14. [14] G. Rebergue, B. Blaysat, H. Chanal, and E. Duc, “In-situ measurement of machining part deflection with Digital Image Correlation,” Measurement, Vol.187, Article No.110301, 2022. https://doi.org/10.1016/j.measurement.2021.110301
  15. [15] S. Wojciechowski, M. Wiackiewicz, and G. M. Krolczyk, “Study on metrological relations between instant tool displacements and surface roughness during precise ball end milling,” Measurement, Vol.129, pp. 686-694, 2018. https://doi.org/10.1016/j.measurement.2018.07.058
  16. [16] E. Diez, H. Perez, J. Marquez, and A. Vizan, “Feasibility study of in-process compensation of deformations in flexible milling,” Int. J. of Machine Tools and Manufacture, Vol.94, pp. 1-14, 2015. https://doi.org/10.1016/j.ijmachtools.2015.03.008
  17. [17] K. Kaneko, A. Kudo, T. Waizumi, J. Shimizu, L. Zhou, H. Ojima, and T. Onuki, “Practical method for identifying model parameters for machining error simulation in end milling through sensor-less monitoring and on-machine measurement,” Int. J. Automation Technol., Vol.18, No.3, pp. 342-351, 2024. https://doi.org/10.20965/ijat.2024.p0342
  18. [18] T. Huang, X. M. Zhang, and H. Ding, “Tool orientation optimization for reduction of vibration and deformation in ball-end milling of thin-walled impeller blades,” Procedia CIRP, Vol.58, pp. 210-215, 2017. https://doi.org/10.1016/j.procir.2017.03.211
  19. [19] M. Habibi, B. Arezoo, and M. V. Nojedeh, “Tool deflection and geometrical error compensation by tool path modification,” Int. J. of Machine Tools & Manufacture, Vol.51, pp. 439-449, 2011. https://doi.org/10.1016/j.ijmachtools.2011.01.009
  20. [20] N. Zeroudi and M. Fontaine, “Prediction of tool deflection and tool path compensation in ball-end milling,” J. of Intelligent Manufacturing, Vol.26, pp. 425-445, 2015. https://doi.org/10.1007/s10845-013-0800-8
  21. [21] X. Duan, F. Peng, K. Zhu, and G. Jiang, “Tool orientation optimization considering cutter deflection error caused by cutting force for multi-axis sculptured surface milling,” The Int. J. of Advanced Manufacturing Technology, Vol.103, pp. 1925-1934, 2019. https://doi.org/10.1007/s00170-019-03663-9
  22. [22] K. Kaneko, M. Ihui, and I. Nishida, “Fast simulation of machining error induced by elastic deformation of tool system in end milling,” J. of Advanced Mechanical Design, Systems, and Manufacturing, Vol.17, No.3, Article No.JAMDSM0035, 2023. https://doi.org/10.1299/jamdsm.2023jamdsm0035
  23. [23] K. Ichikawa, H. Saito, J. Kaneko, Y. Okuma, and K. Horio, “Estimation method of machining error on low rigidity workpiece for tool posture planning,” Int. J. Automation Technol., Vol.11, No.6, pp. 964-970, 2017. https://doi.org/10.20965/ijat.2017.p0964
  24. [24] W. Li, L. Wang, and G. Yu, “Force-induced deformation prediction and flexible error compensation strategy in flank milling of thin-walled parts,” J. of Materials Processing Tech., Vol.297, Article No.117258, 2021. https://doi.org/10.1016/j.jmatprotec.2021.117258
  25. [25] K. Kashiwase, H. Tachiya, and Y. Nakai, “Method of compensation for machining error due to the body deformation in order to design compact machine tools,” The Proc. of Design & Systems Conf., Vol.25, 2015 (in Japanese).
  26. [26] X. Zhang, K. F. Ehmann, T. Yu, and W. Wang, “Cutting forces in micro-end-milling processes,” Int. J. of Machine Tools & Manufacture, Vol.107, pp. 21-40, 2016. https://doi.org/10.1016/j.ijmachtools.2016.04.012
  27. [27] B. Lin, L. Wang, Y. Guo, and J. Yao, “Modeling of cutting forces in end milling based on oblique cutting analysis,” The Int. J. of Advanced Manufacturing Technology, Vol.84, pp. 724-736, 2016. https://doi.org/10.1007/s00170-015-7724-8

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

Last updated on Nov. 06, 2025