Enhancement of Accuracy in Sensorless Cutting-Force Estimation by Mutual Compensation of Multi-integrated Cutting-Force Observers

8 Pages Posted: 2 Nov 2021 Last revised: 29 Nov 2021

See all articles by Kaito Isshiki

Kaito Isshiki

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

Taiki Sato

Keio University

Yasuhiro Imabeppu

DMG MORI Co., Ltd.

Naruhiro Irino

DMG MORI Co., Ltd.

Yasuhiro Kakinuma

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

Date Written: December 1, 2021

Abstract

Techniques without external sensors for cutting-force estimation based on the internal information of machine tools are attracting attention from the viewpoints of cost and sustainability. It is known that using a cutting-force observer, which can estimate the cutting force from encoder information and current reference value, is effective. To date, various cutting-force observers have been proposed. However, each cutting-force observer has different characteristics, such as the bandwidth and direction, which can be estimated with high accuracy. Therefore, the variation in the machining conditions causes a decrease in accuracy when estimating the cutting force. In this study, the output data from multiple cutting-force observers were integrated and mutually compensated for by building a linear regression model and applying the least-squares method to determine the calibration factors. The validity of the proposed method was evaluated using end-milling tests. The experimental results showed that the estimation accuracy of the cutting force using the proposed method can be greatly improved in the feed and cross-feed directions compared with the conventional methods.

Keywords: Process monitoring; Linear regression model; Cutting-force observer

Suggested Citation

Isshiki, Kaito and Sato, Taiki and Imabeppu, Yasuhiro and Irino, Naruhiro and Kakinuma, Yasuhiro, Enhancement of Accuracy in Sensorless Cutting-Force Estimation by Mutual Compensation of Multi-integrated Cutting-Force Observers (December 1, 2021). Proceedings of the Machining Innovations Conference for Aerospace Industry (MIC) 2021, Available at SSRN: https://ssrn.com/abstract=3954300 or http://dx.doi.org/10.2139/ssrn.3954300

Kaito Isshiki (Contact Author)

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

Taiki Sato

Keio University

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

Yasuhiro Imabeppu

DMG MORI Co., Ltd.

201 Midai, Iga, Mie 519-1414
Japan

Naruhiro Irino

DMG MORI Co., Ltd.

201 Midai, Iga, Mie 519-1414
Japan

Yasuhiro Kakinuma

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

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