Automatic Chip Detection Using Differnet

5 Pages Posted: 17 Nov 2022 Last revised: 1 Feb 2023

See all articles by Kenta Mizuhara

Kenta Mizuhara

Department of System Design Engineering, Faculty of Science & Technology, Keio University

Makoto Kato

Keio University

Yoko Hirono

DMG MORI Co., Ltd.

Junichiro Okuno

DMG MORI B.U.G., Co., LTD.

Keisuke Yanagihara

DMG MORI B.U.G., Co., LTD.

Yasuhiro Kakinuma

Department of System Design Engineering, Faculty of Science & Technology, Keio University

Date Written: November 30, 2022

Abstract

Chips entwined with workpieces and accumulated on the mechanical chuck in turning processes are cleaned up by operators in the factories, and this process is needed to be automated. In this study, an automatic chip detection system for the autonomous mobile robot (AMR) with a vision sensor is developed using DifferNet which can be trained with only a small amount of normal data. The results showed that the developed model was able to correctly determine the presence or absence of chips on the chuck.

Keywords: Process automation, Machine learning, Chip removal, Turning, Image processing

Suggested Citation

Mizuhara, Kenta and Kato, Makoto and Hirono, Yoko and Okuno, Junichiro and Yanagihara, Keisuke and Kakinuma, Yasuhiro, Automatic Chip Detection Using Differnet (November 30, 2022). Proceedings of the Machining Innovations Conference for Aerospace Industry (MIC) 2022, Available at SSRN: https://ssrn.com/abstract=4259373 or http://dx.doi.org/10.2139/ssrn.4259373

Kenta Mizuhara (Contact Author)

Department of System Design Engineering, Faculty of Science & Technology, Keio University ( email )

Makoto Kato

Keio University ( email )

2-15-45 Mita
Minato-ku
Tokyo, 108-8345
Japan

Yoko Hirono

DMG MORI Co., Ltd. ( email )

201 Midai, Iga, Mie 519-1414
Japan

Junichiro Okuno

DMG MORI B.U.G., Co., LTD. ( email )

201 Midai, Iga, Mie 519-1414
Japan

Keisuke Yanagihara

DMG MORI B.U.G., Co., LTD. ( email )

201 Midai, Iga, Mie 519-1414
Japan

Yasuhiro Kakinuma

Department of System Design Engineering, Faculty of Science & Technology, Keio University ( email )

Do you have a job opening that you would like to promote on SSRN?

Paper statistics

Downloads
34
Abstract Views
94
PlumX Metrics