Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm
In this study, statistical models were developed using the capabilities of Response Surface Methodology (RSM) to predict the surface roughness in high-speed flat end milling of Ti- 6Al-4V under dry cutting conditions. Machining was performed on a five-axis NC milling machine with a high speed att...
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Trans Tech Publications, Switzerland
2010
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| Online Access: | http://irep.iium.edu.my/3109/ http://irep.iium.edu.my/3109/ http://irep.iium.edu.my/3109/ http://irep.iium.edu.my/3109/1/Predicting_and_investigating_surface_response.pdf |
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iium-31092012-01-26T08:23:27Z http://irep.iium.edu.my/3109/ Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm Alam, Md. Shah Amin, A. K. M. Nurul Patwari, Muhammed Anayet Ullah Konneh, Mohamed TJ Mechanical engineering and machinery In this study, statistical models were developed using the capabilities of Response Surface Methodology (RSM) to predict the surface roughness in high-speed flat end milling of Ti- 6Al-4V under dry cutting conditions. Machining was performed on a five-axis NC milling machine with a high speed attachment, using spindle speed, feed rate, and depth of cut as machining variables. The adequacy of the model was tested at 95% confidence interval. Meanwhile, a time trend was observed in residual values between model predictions and experimental data, reflecting little deviations in surface roughness prediction. A very good performance of the RSM model, in terms of agreement with experimental data, was achieved. It is observed that cutting speed has the most significant influence on surface roughness followed by feed and depth of cut. The model can be used for the analysis and prediction of the complex relationship between cutting conditions and the surface roughness in flat end milling of Ti-6Al-4V materials. The developed quadratic prediction model on surface roughness was coupled with the genetic algorithm to optimize the cutting parameters for the minimum surface roughness. Trans Tech Publications, Switzerland 2010 Article PeerReviewed application/pdf en http://irep.iium.edu.my/3109/1/Predicting_and_investigating_surface_response.pdf Alam, Md. Shah and Amin, A. K. M. Nurul and Patwari, Muhammed Anayet Ullah and Konneh, Mohamed (2010) Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm. Advanced Materials Research, 83-86. pp. 1009-1015. ISSN 1022-6680 http://www.scientific.net/AMR.83-86.1009 doi:10.4028/www.scientific.net/AMR.83-86.1009 |
| repository_type |
Digital Repository |
| institution_category |
Local University |
| institution |
International Islamic University Malaysia |
| building |
IIUM Repository |
| collection |
Online Access |
| language |
English |
| topic |
TJ Mechanical engineering and machinery |
| spellingShingle |
TJ Mechanical engineering and machinery Alam, Md. Shah Amin, A. K. M. Nurul Patwari, Muhammed Anayet Ullah Konneh, Mohamed Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm |
| description |
In this study, statistical models were developed using the capabilities of Response
Surface Methodology (RSM) to predict the surface roughness in high-speed flat end milling of Ti-
6Al-4V under dry cutting conditions. Machining was performed on a five-axis NC milling machine
with a high speed attachment, using spindle speed, feed rate, and depth of cut as machining
variables. The adequacy of the model was tested at 95% confidence interval. Meanwhile, a time
trend was observed in residual values between model predictions and experimental data, reflecting
little deviations in surface roughness prediction. A very good performance of the RSM model, in
terms of agreement with experimental data, was achieved. It is observed that cutting speed has the most significant influence on surface roughness followed by feed and depth of cut. The model can be used for the analysis and prediction of the complex relationship between cutting conditions and the surface roughness in flat end milling of Ti-6Al-4V materials. The developed quadratic
prediction model on surface roughness was coupled with the genetic algorithm to optimize the cutting parameters for the minimum surface roughness. |
| format |
Article |
| author |
Alam, Md. Shah Amin, A. K. M. Nurul Patwari, Muhammed Anayet Ullah Konneh, Mohamed |
| author_facet |
Alam, Md. Shah Amin, A. K. M. Nurul Patwari, Muhammed Anayet Ullah Konneh, Mohamed |
| author_sort |
Alam, Md. Shah |
| title |
Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm |
| title_short |
Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm |
| title_full |
Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm |
| title_fullStr |
Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm |
| title_full_unstemmed |
Prediction and investigation of surface response in high speed end milling of Ti-6Al-4V and optimization by genetic algorithm |
| title_sort |
prediction and investigation of surface response in high speed end milling of ti-6al-4v and optimization by genetic algorithm |
| publisher |
Trans Tech Publications, Switzerland |
| publishDate |
2010 |
| url |
http://irep.iium.edu.my/3109/ http://irep.iium.edu.my/3109/ http://irep.iium.edu.my/3109/ http://irep.iium.edu.my/3109/1/Predicting_and_investigating_surface_response.pdf |
| first_indexed |
2023-09-18T20:10:48Z |
| last_indexed |
2023-09-18T20:10:48Z |
| _version_ |
1777407464227995648 |