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...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | en |
| Published: |
2008
|
| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/1241/1/2008_J22_SRE_KKadirgama_M.M.Noor.pdf http://umpir.ump.edu.my/id/eprint/1241/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1831520944790700032 |
|---|---|
| author | K., Kadirgama M. M., Noor |
| author_facet | K., Kadirgama M. M., Noor |
| author_sort | K., Kadirgama |
| building | UMPSA Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaysia Pahang Al-Sultan Abdullah |
| content_source | UMPSA Institutional Repository |
| continent | Asia |
| country | Malaysia |
| 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 |
| id | my.ump.umpir.1241 |
| institution | Universiti Malaysia Pahang |
| language | en |
| publishDate | 2008 |
| record_format | eprints |
| spelling | my.ump.umpir.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. (Published) |
| spellingShingle | TJ Mechanical engineering and machinery K., Kadirgama M. M., Noor Prediction of Tool Life by Statistic Method in End-milling Operation |
| title | 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_short | Prediction of Tool Life by Statistic Method in End-milling
Operation |
| title_sort | prediction of tool life by statistic method in end-milling
operation |
| topic | TJ Mechanical engineering and machinery |
| url | http://umpir.ump.edu.my/id/eprint/1241/1/2008_J22_SRE_KKadirgama_M.M.Noor.pdf http://umpir.ump.edu.my/id/eprint/1241/ |
| url_provider | http://umpir.ump.edu.my/ |