Online cutting tool wear monitoring using I-kaz method and new regression model

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals using the regression model and I-kaz method. The detection of tool wear was done automatically using the in-house developed regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out on a CNC turning machine Colchester Master Tornado T4 in dry cutting condition, and Kistler 9255B dynamometer was used to measure the cutting force signals, which then stored and displayed in the DasyLab software. The progression of the cutting tool flank wear land (VB) was indicated by the amount of the cutting force generated. Later, the I-kaz was used to analyze all the cutting force signals from beginning of the cut until the rejection stage of the cutting tool. Results of the I-Kaz analysis were represented by various characteristic of I-kaz 3D coefficient and 3D graphic presentation. The I-kaz 3D coefficient number decreases as the tool wear increases. This method can be used for real time tool wear monitoring

Original languageEnglish
Title of host publicationAdvanced Materials Research
Pages738-743
Number of pages6
Volume126-128
DOIs
Publication statusPublished - 2010
Event13th International Symposium on Advances in Abrasive Technology, ISAAT2010 - Taipei
Duration: 19 Sep 201022 Sep 2010

Publication series

NameAdvanced Materials Research
Volume126-128
ISSN (Print)10226680

Other

Other13th International Symposium on Advances in Abrasive Technology, ISAAT2010
CityTaipei
Period19/9/1022/9/10

Fingerprint

Cutting tools
Wear of materials
Monitoring
Machining
Tornadoes
Dynamometers

Keywords

  • I-kaz method
  • Mathematical model
  • Online tool wear monitoring

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Online cutting tool wear monitoring using I-kaz method and new regression model. / A Ghani, Jaharah; Rizal, Muhammad; Nuawi, Mohd. Zaki; Che Haron, Che Hassan; Ghazali, Mariyam Jameelah; Ab Rahman, Mohd Nizam.

Advanced Materials Research. Vol. 126-128 2010. p. 738-743 (Advanced Materials Research; Vol. 126-128).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

A Ghani, J, Rizal, M, Nuawi, MZ, Che Haron, CH, Ghazali, MJ & Ab Rahman, MN 2010, Online cutting tool wear monitoring using I-kaz method and new regression model. in Advanced Materials Research. vol. 126-128, Advanced Materials Research, vol. 126-128, pp. 738-743, 13th International Symposium on Advances in Abrasive Technology, ISAAT2010, Taipei, 19/9/10. https://doi.org/10.4028/www.scientific.net/AMR.126-128.738
@inproceedings{597b5172e54b44fc85d6c77d633b9d14,
title = "Online cutting tool wear monitoring using I-kaz method and new regression model",
abstract = "This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals using the regression model and I-kaz method. The detection of tool wear was done automatically using the in-house developed regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out on a CNC turning machine Colchester Master Tornado T4 in dry cutting condition, and Kistler 9255B dynamometer was used to measure the cutting force signals, which then stored and displayed in the DasyLab software. The progression of the cutting tool flank wear land (VB) was indicated by the amount of the cutting force generated. Later, the I-kaz was used to analyze all the cutting force signals from beginning of the cut until the rejection stage of the cutting tool. Results of the I-Kaz analysis were represented by various characteristic of I-kaz 3D coefficient and 3D graphic presentation. The I-kaz 3D coefficient number decreases as the tool wear increases. This method can be used for real time tool wear monitoring",
keywords = "I-kaz method, Mathematical model, Online tool wear monitoring",
author = "{A Ghani}, Jaharah and Muhammad Rizal and Nuawi, {Mohd. Zaki} and {Che Haron}, {Che Hassan} and Ghazali, {Mariyam Jameelah} and {Ab Rahman}, {Mohd Nizam}",
year = "2010",
doi = "10.4028/www.scientific.net/AMR.126-128.738",
language = "English",
isbn = "9780878492428",
volume = "126-128",
series = "Advanced Materials Research",
pages = "738--743",
booktitle = "Advanced Materials Research",

}

TY - GEN

T1 - Online cutting tool wear monitoring using I-kaz method and new regression model

AU - A Ghani, Jaharah

AU - Rizal, Muhammad

AU - Nuawi, Mohd. Zaki

AU - Che Haron, Che Hassan

AU - Ghazali, Mariyam Jameelah

AU - Ab Rahman, Mohd Nizam

PY - 2010

Y1 - 2010

N2 - This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals using the regression model and I-kaz method. The detection of tool wear was done automatically using the in-house developed regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out on a CNC turning machine Colchester Master Tornado T4 in dry cutting condition, and Kistler 9255B dynamometer was used to measure the cutting force signals, which then stored and displayed in the DasyLab software. The progression of the cutting tool flank wear land (VB) was indicated by the amount of the cutting force generated. Later, the I-kaz was used to analyze all the cutting force signals from beginning of the cut until the rejection stage of the cutting tool. Results of the I-Kaz analysis were represented by various characteristic of I-kaz 3D coefficient and 3D graphic presentation. The I-kaz 3D coefficient number decreases as the tool wear increases. This method can be used for real time tool wear monitoring

AB - This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals using the regression model and I-kaz method. The detection of tool wear was done automatically using the in-house developed regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out on a CNC turning machine Colchester Master Tornado T4 in dry cutting condition, and Kistler 9255B dynamometer was used to measure the cutting force signals, which then stored and displayed in the DasyLab software. The progression of the cutting tool flank wear land (VB) was indicated by the amount of the cutting force generated. Later, the I-kaz was used to analyze all the cutting force signals from beginning of the cut until the rejection stage of the cutting tool. Results of the I-Kaz analysis were represented by various characteristic of I-kaz 3D coefficient and 3D graphic presentation. The I-kaz 3D coefficient number decreases as the tool wear increases. This method can be used for real time tool wear monitoring

KW - I-kaz method

KW - Mathematical model

KW - Online tool wear monitoring

UR - http://www.scopus.com/inward/record.url?scp=78650947653&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78650947653&partnerID=8YFLogxK

U2 - 10.4028/www.scientific.net/AMR.126-128.738

DO - 10.4028/www.scientific.net/AMR.126-128.738

M3 - Conference contribution

SN - 9780878492428

VL - 126-128

T3 - Advanced Materials Research

SP - 738

EP - 743

BT - Advanced Materials Research

ER -