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

Paper:

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

Received:
November 1, 2017
Accepted:
September 14, 2018
Published:
January 5, 2019
Keywords:
monitoring, tool deflection, end-milling, CCD image, in-process
Abstract

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:
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