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IJAT Vol.7 No.3 pp. 337-344
doi: 10.20965/ijat.2013.p0337
(2013)

Paper:

Using Pulse Laser Processing to Shape Cutting Edge of PcBN Tool for High-Precision Turning of Hardened Steel

Daisuke Suzuki*, Fumihiro Itoigawa*, Keiichi Kawata**,
and Takashi Nakamura*

*Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, Aichi 466-8555, Japan

**Aichi Center for Industry and Science Technology, 157-1, Onda-cho, Kariya-shi, Aichi 470-0356, Japan

Received:
December 13, 2012
Accepted:
March 11, 2013
Published:
May 5, 2013
Keywords:
high-precision turning, PcBN cutting tool, pulse laser, hardened steel
Abstract

Polycrystalline Cubic Boron Nitride (PcBN) cutting tools have excellent characteristics, such as a high degree of hardness and low chemical reactivity, so they have the potential to replace the high precision grinding of hardened steel with high precision cutting. However, there are some problems inherent in so-called sintered materials, including low formability and unsteady wear. In order to solve these problems, pulsed laser processing is applied to shape a cutting edge. In this study, first PcBN cutting tools processed by lasers are adopted to the high-precision turning of hardened steel with 58HRC. As the result, these PcBN cutting tools provide a steady cutting state and a smoother finished surface. Second, in order to investigate these advantages of PcBN cutting tools processed by laser, individual requirements of the cutting tool are investigated: edge sharpness, surface quality including micro-defects, surface hardness, and friction coefficient. The results indicate that tools processed by laser have sharper edges and smoother, harder, and lowerfiction surfaces, compared to ground tools. Above all, the increase in surface hardness improves cutting performance because of it provides higher wear resistance.

Cite this article as:
D. Suzuki, F. Itoigawa, K. Kawata, and <. Nakamura, “Using Pulse Laser Processing to Shape Cutting Edge of PcBN Tool for High-Precision Turning of Hardened Steel,” Int. J. Automation Technol., Vol.7, No.3, pp. 337-344, 2013.
Data files:
References
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Last updated on Nov. 19, 2019