Prediction of Tool Life by Statistic Method in End-milling Operation

The aim of the this study is to develop the tool life prediction model for P20 tool steel with aid of statistical method, using coated carbide cutting tool under various cutting conditions. This prediction model was then compared with the results obtained experimentally. By using Response Surface...

Full description

Bibliographic Details
Main Authors: K., Kadirgama, M. M., Noor
Format: Article
Language:English
Published: 2008
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/1241/
http://umpir.ump.edu.my/id/eprint/1241/1/2008_J22_SRE_KKadirgama_M.M.Noor.pdf
id ump-1241
recordtype eprints
spelling ump-12412018-01-31T02:17:43Z http://umpir.ump.edu.my/id/eprint/1241/ Prediction of Tool Life by Statistic Method in End-milling Operation K., Kadirgama M. M., Noor TJ Mechanical engineering and machinery The aim of the this study is to develop the tool life prediction model for P20 tool steel with aid of statistical method, using coated carbide cutting tool under various cutting conditions. This prediction model was then compared with the results obtained experimentally. By using Response Surface Method (RSM) of experiment, first and second order models were developed with 95% confidence level. The tool life was developed in terms of cutting speed, feed rate, axial depth and radial depth, using RSM and design of experiment. In general, the results obtained from the mathematical model are in good agreement with that obtained from the experiment data’s. It was found that the feedrate, cutting speed, axial depth and radial depth played a major role in determining the tool life. On the other hand, the tool life increases with a reduction in cutting speed and feedrate. For end-milling of P20 tool steel, the optimum conditions that is required to maximize the coated carbide tool life are as follow: cutting speed of 140 m/s, federate of 0.1 mm/rev, axial depth of 1.5 mm and radial depth of 2 mm. Using these parameters, a tool life of 39.46 min was obtained. 2008 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/1241/1/2008_J22_SRE_KKadirgama_M.M.Noor.pdf K., Kadirgama and M. M., Noor (2008) Prediction of Tool Life by Statistic Method in End-milling Operation. Scientific Research and Essay , 3 (5). pp. 180-186. ISSN 1992-2248
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic TJ Mechanical engineering and machinery
spellingShingle TJ Mechanical engineering and machinery
K., Kadirgama
M. M., Noor
Prediction of Tool Life by Statistic Method in End-milling Operation
description The aim of the this study is to develop the tool life prediction model for P20 tool steel with aid of statistical method, using coated carbide cutting tool under various cutting conditions. This prediction model was then compared with the results obtained experimentally. By using Response Surface Method (RSM) of experiment, first and second order models were developed with 95% confidence level. The tool life was developed in terms of cutting speed, feed rate, axial depth and radial depth, using RSM and design of experiment. In general, the results obtained from the mathematical model are in good agreement with that obtained from the experiment data’s. It was found that the feedrate, cutting speed, axial depth and radial depth played a major role in determining the tool life. On the other hand, the tool life increases with a reduction in cutting speed and feedrate. For end-milling of P20 tool steel, the optimum conditions that is required to maximize the coated carbide tool life are as follow: cutting speed of 140 m/s, federate of 0.1 mm/rev, axial depth of 1.5 mm and radial depth of 2 mm. Using these parameters, a tool life of 39.46 min was obtained.
format Article
author K., Kadirgama
M. M., Noor
author_facet K., Kadirgama
M. M., Noor
author_sort K., Kadirgama
title Prediction of Tool Life by Statistic Method in End-milling Operation
title_short Prediction of Tool Life by Statistic Method in End-milling Operation
title_full Prediction of Tool Life by Statistic Method in End-milling Operation
title_fullStr Prediction of Tool Life by Statistic Method in End-milling Operation
title_full_unstemmed Prediction of Tool Life by Statistic Method in End-milling Operation
title_sort prediction of tool life by statistic method in end-milling operation
publishDate 2008
url http://umpir.ump.edu.my/id/eprint/1241/
http://umpir.ump.edu.my/id/eprint/1241/1/2008_J22_SRE_KKadirgama_M.M.Noor.pdf
first_indexed 2023-09-18T21:54:12Z
last_indexed 2023-09-18T21:54:12Z
_version_ 1777413970199576576