eprintid: 15254
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/52/54
datestamp: 2023-11-10 03:29:52
lastmod: 2023-11-10 03:29:52
status_changed: 2023-11-10 01:59:02
type: article
metadata_visibility: show
creators_name: Fong, K.M.
creators_name: Wang, X.
creators_name: Kamaruddin, S.
creators_name: Ismadi, M.-Z.
title: Investigation on universal tool wear measurement technique using image-based cross-correlation analysis
ispublished: pub
keywords: Carbide cutting tools; Carbides; Correlation methods; Image analysis; Image enhancement; Machining; Monitoring; Productivity; Wear of materials, Cross correlations; Cross-correlation analysis; Intelligent machining; Machining productivity; Measurement system; Monitoring techniques; Off-line monitoring; Quantitative images, Cutting tools
note: cited By 33
abstract: Early detection of tool defects enables proactive prevention of disruption, thus increasing productivity, maintaining quality and agility that brings significant competitive value to the organization. Hence, an effective tool wear monitoring system is vital for intelligent machining process. With the aim to develop an on-machine universal offline monitoring system, a novel quantitative image-based tool wear measurement system based on cross correlation analysis, is proposed to measure tool wear directly from the machining workbench. The sensitivity and accuracy of the proposed technique were further improved through cross-covariance analysis of original and worn tool images. Analyses on various wear conditions of drill bit, end mill, taper tap and carbide insert demonstrated the high effectiveness of the developed measurement system, reflected in the cross-correlation graphs pattern with wear measurement at a microscale down to 100 µm. The cross-correlation based measurement enables optimization of the machining productivity through just-in-time tool change through effective monitoring technique. © 2020 Elsevier Ltd
date: 2021
publisher: Elsevier B.V.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092113694&doi=10.1016%2fj.measurement.2020.108489&partnerID=40&md5=91ea135d9f3a7ac2621e48eccba47224
id_number: 10.1016/j.measurement.2020.108489
full_text_status: none
publication: Measurement: Journal of the International Measurement Confederation
volume: 169
refereed: TRUE
issn: 02632241
citation:   Fong, K.M. and Wang, X. and Kamaruddin, S. and Ismadi, M.-Z.  (2021) Investigation on universal tool wear measurement technique using image-based cross-correlation analysis.  Measurement: Journal of the International Measurement Confederation, 169.   ISSN 02632241