single-au.php

IJAT Vol.10 No.5 pp. 767-772
doi: 10.20965/ijat.2016.p0767
(2016)

Paper:

In-Process Tool Wear Detection of Uncoated Square End Mill Based on Electrical Contact Resistance

Amine Gouarir*,†, Syuhei Kurokawa*, Takao Sajima*, and Mitsuaki Murata**

*Department of Mechanical Engineering, Kyushu University
744 Motooka, Nishi-ku, Fukuoka 819-0395, Japan

Corresponding author

**Department of Mechanical Engineering, Kyushu Sangyo University, Japan

Received:
February 6, 2016
Accepted:
June 17, 2016
Published:
September 5, 2016
Keywords:
electric contact resistance, in-process monitoring, solid and throw-away square end mill, flank wear, electromotive force
Abstract
This paper presents a method for in-process detection of tool wear in square end mills. The developed high-speed tool wear detection system uses the contact resistance between the tool and workpiece as a gauge to monitor the progression of tool wear. The electrical resistance decreases with an increase in contact area on the tool flank. In the experiments conducted in our previous study, the target was the face milling process. In the present study, the experiments were conducted on down cut milling with a square end mill. The results are presented based on the observations made on the relationship between the area of tool flank wear and tool-work contact resistance. In conclusion, the results of the experiment show that the present tool wear detection system is effective as an in-process tool wear detection system for square end mills.
Cite this article as:
A. Gouarir, S. Kurokawa, T. Sajima, and M. Murata, “In-Process Tool Wear Detection of Uncoated Square End Mill Based on Electrical Contact Resistance,” Int. J. Automation Technol., Vol.10 No.5, pp. 767-772, 2016.
Data files:
References
  1. [1] S. Kurada and C. Bradley, “A review of machine vision sensors for tool condition monitoring,” Computers in Industry, Vol.34, No.1, pp. 55-72, 1997.
  2. [2] S. Ibaraki, A. Matsubara, and M. Murozumi, “Efficiency Comparison of Cutting Strategies for End Milling Processes Under Feedrate Scheduling,” Int. Journal of Automation Technology, Vol.2, No.5, pp. 377-383.
  3. [3] T. Matsumura, M. Shimada, K. Teramoto, and E. Usui, “Predictive Cutting Force Model and Cutting Force Chart for Milling with Cutter Axis Inclination,” Int. Journal of Automation Technology, Vol.7, No.1, pp. 30-38.
  4. [4] S. Y. Liang and D. A. Dornfeld, “Tool wear Detection using Time series Analysis of Acoustic Emission,” Journal of Engineering for Industry, Vol.11, No.205, 1989.
  5. [5] W. H. Wang, G. S. Hong, Y. S. Wong, and K. P. Zhu, “Sensor fusion for on-line tool condition monitoring in milling,” Int. Journal of Production Research, Vol.45, No.21, pp. 5095-5116, 2007 (in press).
  6. [6] Z. Kunpeng, W. Y. San, and H. G. Soon, “Wavelet analysis of sensor signals for tool condition monitoring: A review and some new results,” Int. J. Adv. Manuf. Technol., Vol.49, pp. 537-553, 2009.
  7. [7] S. C. Lin and R. J. Lin, “Tool wear monitoring in face milling using force signals,” Wear, Vol.198, No.1-2, pp. 136-142, 1996.
  8. [8] D. E. Dimla Snr., “Tool wear monitoring using cutting force measurements,” 15th NCMR: Advances in Manufacturing Technology XIII, pp. 33-37, 1999.
  9. [9] K. Nakamoto, S. Mitsuhashi, K. Adachi, and K. Shirase, “A Machine Tool Spindle Achieving Real-Time Balancing Using Magnetic Fluid,” Int. Journal of Automation Technology, Vol.3, No.2, pp. 193-198.
  10. [10] 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. Journal of Automation Technology, Vol.5, No.3, pp. 362-368.
  11. [11] M. Fujimoto, Y. Wu, M. Nomura, H. Kanai, and M. Jin, “Wear Behavior of Grain Cutting Edge in Ultrasonic Assisted Grinding Using Mini-Size Wheel,” Int. Journal of Automation Technology, Vol.9, No.4, pp. 365-372.
  12. [12] E. Kuljanic and M. Sortino, “TWEM: A method based on cutting forces-monitoring tool wear in face milling,” Int. J. Mach. Tools Manuf., Vol.45, pp. 29-34, 2005.
  13. [13] J. Srinivas and K. R. Kotaiah, “Tool wear monitoring with indirect Alloy,” CIRP Annals – Manufacturing Technology, Vol.54, No.1, pp. 7174, 2005.
  14. [14] H. Suzuki, M. Okada, K. Okada, and Y. Ito, “Precision Cutting of Ceramics with Milling Tool of Single Crystalline Diamond,” Int. Journal of Automation Technology, Vol.9, No.1, pp. 26-32.
  15. [15] R. Tanaka, A. Hosokawa, T. Furumoto, and T. Ueda, “Effects of Tool Edge Geometry on Cutting Temperature in Continuous Cutting of Case Hardened Steel,” Int. Journal of Automation Technology, Vol.7, No.3, pp. 313-320.
  16. [16] S. Maegawa, Y. Morikawa, S. Hayakawa, F. Itoigawa, and T. Nakamura, “Effects of Fiber Orientation Direction on Tool-Wear Processes in Down-Milling of Carbon Fiber-Reinforced Plastic Laminates,” Int. Journal of Automation Technology, Vol.9, No.4, pp. 356-364.
  17. [17] B. Denkena, J. Köhler, R. Meyer, and J. H. Stiffel, “Modification of the Tool-Workpiece Contact Conditions to Influence the Tool Wear and Workpiece Loading During Hard Turning,” Int. Journal of Automation Technology, Vol.5, No.3, pp. 353-361.
  18. [18] M. Murata, S. Kurokawa, O. Ohnishi, M. Uneda, and T. Doi, “Real-Time Evaluation of Tool Flank Wear by In-Process Contact Resistance Measurement in Face Milling,” Journal of Advanced Mechanical Design, System and Manufacturing, Vol.6, No.6, pp. 958-970, 2012.
  19. [19] K. J. Lee, T. M Lee, and M. Y. Yang, “Tool wear monitoring system for CNC end milling using a hybrid approach to cutting force regulation,” Int. J. Adv. Manuf. Technol., Vol.32, pp. 8-17, 2007.
  20. [20] A. Gouarir, S. Kurokawa, M. Murata, and H. Fujiwara, “Performance analysis of high speed tool wear detection system,,” Proc. ADCONIP 2014.
  21. [21] M. Murata, S. Kurokawa, O. Ohnishi, M. Uneda, and T. Doi, “Development of High Speed Tool Wear Detection System by using DC Two-Terminal Methods,” Proc. of the 9th Cooperative and Joint Int. Conf. on Ultra-precision Machining Process 2013, pp. 72-76, 2013.

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

Last updated on Apr. 18, 2024