Predicting surface roughness with respect to process parameters using Regression Analysis Models in end milling
Surface roughness affects the functional attributes of finished parts. Therefore, predicting the finish surface is important to select the cutting levels in order to reach the required quality. In this research an experimental investigation was conducted to predict the surface roughness in the fi...
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2012
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my.iium.irep.292252013-05-30T05:11:37Z http://irep.iium.edu.my/29225/ Predicting surface roughness with respect to process parameters using Regression Analysis Models in end milling Adesta, Erry Yulian Triblas Al Hazza, Muataz Hazza Faizi Suprianto, Mohamad Yuhan Riza, Muhammad TA Engineering (General). Civil engineering (General) Surface roughness affects the functional attributes of finished parts. Therefore, predicting the finish surface is important to select the cutting levels in order to reach the required quality. In this research an experimental investigation was conducted to predict the surface roughness in the finish end milling process with higher cutting speed. Twenty sets of data for finish end milling on AISI H13 at hardness of 48 HRC have been collected based on five-level of Central Composite Design (CCD). All the experiments done by using indexable tool holder Sandvick Coromill R490 and the insert was PVD coated TiAlN carbide. The experimental work performed to predict four different roughness parameters; arithmetic mean roughness (Ra), total roughness (Rt), mean depth of roughness (Rz) and the root mean square (Rq). Trans Tech Publications, Switzerland 2012 Article REM application/pdf en http://irep.iium.edu.my/29225/1/Predicting_Surface_Roughness_with_Respect_to_Process_Parameters.pdf Adesta, Erry Yulian Triblas and Al Hazza, Muataz Hazza Faizi and Suprianto, Mohamad Yuhan and Riza, Muhammad (2012) Predicting surface roughness with respect to process parameters using Regression Analysis Models in end milling. Advanced Materials Research, 576. pp. 99-102. ISSN 1022-6680 10.4028/www.scientific.net/AMR.576.99 |
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TA Engineering (General). Civil engineering (General) Adesta, Erry Yulian Triblas Al Hazza, Muataz Hazza Faizi Suprianto, Mohamad Yuhan Riza, Muhammad Predicting surface roughness with respect to process parameters using Regression Analysis Models in end milling |
description |
Surface roughness affects the functional attributes of finished parts. Therefore, predicting
the finish surface is important to select the cutting levels in order to reach the required quality. In
this research an experimental investigation was conducted to predict the surface roughness in the
finish end milling process with higher cutting speed. Twenty sets of data for finish end milling on
AISI H13 at hardness of 48 HRC have been collected based on five-level of Central Composite
Design (CCD). All the experiments done by using indexable tool holder Sandvick Coromill R490
and the insert was PVD coated TiAlN carbide. The experimental work performed to predict four
different roughness parameters; arithmetic mean roughness (Ra), total roughness (Rt), mean depth
of roughness (Rz) and the root mean square (Rq). |
format |
Article |
author |
Adesta, Erry Yulian Triblas Al Hazza, Muataz Hazza Faizi Suprianto, Mohamad Yuhan Riza, Muhammad |
author_facet |
Adesta, Erry Yulian Triblas Al Hazza, Muataz Hazza Faizi Suprianto, Mohamad Yuhan Riza, Muhammad |
author_sort |
Adesta, Erry Yulian Triblas |
title |
Predicting surface roughness with respect to process parameters using Regression Analysis Models in end milling |
title_short |
Predicting surface roughness with respect to process parameters using Regression Analysis Models in end milling |
title_full |
Predicting surface roughness with respect to process parameters using Regression Analysis Models in end milling |
title_fullStr |
Predicting surface roughness with respect to process parameters using Regression Analysis Models in end milling |
title_full_unstemmed |
Predicting surface roughness with respect to process parameters using Regression Analysis Models in end milling |
title_sort |
predicting surface roughness with respect to process parameters using regression analysis models in end milling |
publisher |
Trans Tech Publications, Switzerland |
publishDate |
2012 |
url |
http://irep.iium.edu.my/29225/1/Predicting_Surface_Roughness_with_Respect_to_Process_Parameters.pdf http://irep.iium.edu.my/29225/ |
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13.18916 |