IJAT Vol.13 No.1 pp. 133-140
doi: 10.20965/ijat.2019.p0133


Monitoring of Cutting State in End-Milling Based on Measurement of Tool Behavior Using CCD Image

Shinichi Yoshimitsu, Daiki Iwashita, Kenji Shimana, Yuya Kobaru, and Shunichi Yamashita

National Institute of Technology, Kagoshima College
1460-1 Shinko, Hayato-cho, Kirishima-shi, Kagoshima 899-5193, Japan

Corresponding author

November 1, 2017
September 14, 2018
January 5, 2019
monitoring, tool deflection, end-milling, CCD image, in-process

To date, various in-process monitoring and measuring techniques for milling have been proposed; these are based on factors such as spindle power, cutting force, and vibration. However, the spindle power and cutting force in small-diameter milling processes are too small, thereby rendering these methods ineffective. This study aims to develop an in-process monitoring system of the cutting state, and thus, prevent tool breakage in milling when using a small-diameter tool. Our previous study showed that this monitoring technique is based on the analysis of the tool projection image by a CCD camera. It enables a precise measurement of tool deflection during high-speed milling. In this study, we apply this system to the measurement of tool deflection in end milling under different cutting conditions, including tool type, machining shape, workpiece, and feed rate. Moreover, we examine the relationship between tool deflection and cutting conditions. The results clarify that this system enables in-process monitoring of tool deflection. The measured tool deflection with this system is influenced by the cutting condition. In addition, the tool deflection shows a periodical change in one turn, which seems to be related to the number of tool edges.

Cite this article as:
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.
Data files:
  1. [1] L. H. Zhao et al., “Research on Tool Wear Form in Micro Turn-Milling Process,” Applied Mechanics and Materials, Vols.184-185, pp. 663-667, 2012.
  2. [2] F. Klocke, S. Kratz, T. Auerbach, S. Gierlings, G. Wirtz, and D. Veselovac, “Process Monitoring and Control of Machining Operations,” Int. J. Automation Technol., Vol.5, No.3, pp. 403-411, 2011.
  3. [3] T. Matsumura, T. Murayama, and E. Usui, “Tool Wear Monitoring System in Milling Operation,” J. JSPE, Vol.65, No.11, pp. 1617-1622, 1999 (in Japanese).
  4. [4] M. S. Alajmi and S. E. Oraby, “Using Infrared Thermograph of Chip Temperature to Monitor Cutting Edge Performance,” Applied Mechanics and Materials, Vols.789-790, pp. 549-553, 2015.
  5. [5] N. Sawai, J. Song, and H. Park, “Automated Measuremnet of Tool Wear using an Image Processing System,” J. JSPE, Vol.61, No.3, pp. 368-371, 1995 (in Japanese).
  6. [6] A. Matsubara and S. Ibaraki, “Monitoring and Control of Cutting Forces in Machining Processes,” Int. J. Automation Technol., Vol.3, No.4, pp. 445-456, 2009.
  7. [7] P. Wang, J. Xin, J. Li, and S. Yin, “Research on Tool Cutting Monitoring System Based on Cutting Force and Workpiece Surface Image Texture,” J. Applied Mechanics and Materials. Vols.16-19, pp. 960-964, 2009.
  8. [8] P. Khajornrungruang, K. Kimura, Y. Takaya, and K. Suzuki, “High Precision Tool Cutting Edge Monitoring Using Laser Diffraction for On-Machine Measurement,” Int. J. Automation Technol., Vol.6, No.2, pp. 163-167, 2012.
  9. [9] H. Nakagawa, Y. Kurita et al., “Experimental Analysis of Chatter Vibration in End-Milling Using Laser Doppler Vibrometers,” Int. J. Automation Technol., Vol.2, No.6, pp. 431-438, 2008.
  10. [10] M. Hirao, A. Terashima, H.-Y. Joo et al., “Behavior of cutting heat in high speed cutting,” J. JSPE, Vol.64, No.7, pp. 1067-1071, 1998 (in Japanese).
  11. [11] M. Sato and H. Tanaka, “Radiotional Thermometry of Tool Tip Temperature in End Milling,” Proc. JSPE Autumn Meeting 2007, pp. 567-568, 2007 (in Japanese).
  12. [12] M. Wada and M. Mizuno, “Studies on Friction and Wear Utilizing Acoustic Emission : Relation between Friction and Wear Mode and Acoustic Emission Signals,” J. JSPE, Vol.54, No.4, pp. 673-678, 1989 (in Japanese).
  13. [13] H. Yoshioka, M. Hayashi, and H. Shinno, “Status Monitoring of Ultraprecision Machining Using Micro Thermo Sensor and AE Sensor,” Int. J. Automation Technol., Vol.3, No.4, pp. 422-427, 2009.
  14. [14] H. Hashizume, H. Shinno, and Y. Ito, “In-process Monitoring Method for Machining Environment Using Multifunctional Compact Sensor,” Trans. JSME, Series C, Vol.64, No.619, pp. 1072-1076, 1998.
  15. [15] L. Guo, S. Li, M. Zhang, and T. Gao, “Tool Wear Monitoring in Advanced Manufacture System Based on Multi-source Information Fusion,” Proc. 8th ICPMT, pp. 289-292, 2006.
  16. [16] D. Kurihara, Y. Kakinuma, and S. Katsura, “Sensorless Cutting Force Monitoring Using Parallel Disturbance Observer,” Int. J. Automation Technol., Vol.3, No.4, pp. 415-421, 2009.
  17. [17] H. Sawano, R. Kobayashi, H. Yoshioka, and H. Shinno, “A Proposed Ultraprecision Machining Process Monitoring Method Using Causal Network Model of Air Spindle System,” Int. J. Automation Technol., Vol.5, No.3, pp. 362-368, 2011.
  18. [18] K. Enomoto, M. Takei, and Y. Kakinuma, “Real-Time Cutting Force/Torque Prediction During Turning,” Int. J. Automation Technol., Vol.6, No.5, pp. 669-674, 2012.
  19. [19] T. Beno, J. Repo, and L. Pejryd, “The Use of Machine Tool Internal Encoders as Sensors in a Process Monitoring System,” Int. J. Automation Technol., Vol.7, No.4. pp. 410-417, 2013.
  20. [20] S. Yoshimitsu, S. Satonaka et al., “In-process Monitoring of Tool Behavior and Tool Wear in End Milling by Use of Projection Image,” J. Key Engineering Materials, Vols.523-524, pp. 433-438, 2012.

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

Last updated on Jul. 19, 2024