Tool wear and tool life estimation based on linear regression learning

Title

Tool wear and tool life estimation based on linear regression learning

Creator

Karuppusamy N.S.; Pal Pandian P.; Lee H.-S.; Kang B.-Y.

Description

Tools have remained an integral part of the society without which stimulation of certain aspects of human evolution would not have been possible. In recent times the modern tools are used in the manufacturing of high precision components. We know that the accuracy and surface finish of these components can be achieved only by the usage of accurate tools. Sharp edged tools may loosen their sharpness due to repeated usage and machining parameters. Hence to address this issue we propose a system to monitor tool wear by using the captured image of cutting tool tip. We used vision system since it is the primitive method of predicting tool wear and two main machining parameters feed rate and depth of cut. The image of flank wear cutting edge at tool tip is captured by examining under profile projector. The system uses linear regression model to calculate tool wear which is mapped onto continuous 2-D coordinates with feed rate and depth of cut as axis from a captured digital image. Thus the proposed intelligent system uses profile projector and digital image processing methods to estimate tool wear continuously and predictively like humans rather than using strict rules. By estimating tool wear continuously the machine can better perform and machine components accurately by using the resultant values of feed rate and depth of cut as a threshold which are arrived as a result. 2015 IEEE.

Source

2015 IEEE International Conference on Mechatronics and Automation, ICMA 2015, pp. 17-21.

Date

2015-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Depth of Cut; Feed Rate; Flank Wear; Linear Regression; Tool Wear

Coverage

Karuppusamy N.S., Department of Mechanical Engineering, Christ University, Bangalore, 560 060, India; Pal Pandian P., Department of Mechanical Engineering, Christ University, Bangalore, 560 060, India; Lee H.-S., School of Mechanical Engineering, Kyungpook National University, Daegu, 702-701, South Korea; Kang B.-Y., School of Mechanical Engineering, Kyungpook National University, Daegu, 702-701, South Korea

Rights

Restricted Access

Relation

ISBN: 978-147997096-4

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICMA.2015.7237449

https://www.scopus.com/inward/record.uri?eid=2-s2.0-84955328314&doi=10.1109%2fICMA.2015.7237449&partnerID=40&md5=b0531682efc4cdcf66d5ac48df0792b7