Surface roughness modeling in high speed hard turning using regression analysis

Surface roughness plays an important role in the final quality of the machining parts. Therefore, predicting and simulating the roughness before the machining process is an important issue. The purpose of this research is to develop a reliable model for predicting and simulating the average surface...

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Main Authors:	Al Hazza, Muataz Hazza Faizi, Adesta, Erry Yulian Triblas, Hassan, Muhammad Hasibul, Shaffiar, Norhashimah
Format:	Article
Language:	English English
Published:	Praise Worthy Prize 2014
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/36862/ http://irep.iium.edu.my/36862/ http://irep.iium.edu.my/36862/1/017-Al_Hazza_def_15204_-1.pdf http://irep.iium.edu.my/36862/4/36862_Surface%20roughness_scopus.pdf

id	iium-36862
recordtype	eprints
spelling	iium-368622017-09-19T08:32:08Z http://irep.iium.edu.my/36862/ Surface roughness modeling in high speed hard turning using regression analysis Al Hazza, Muataz Hazza Faizi Adesta, Erry Yulian Triblas Hassan, Muhammad Hasibul Shaffiar, Norhashimah T Technology (General) Surface roughness plays an important role in the final quality of the machining parts. Therefore, predicting and simulating the roughness before the machining process is an important issue. The purpose of this research is to develop a reliable model for predicting and simulating the average surface roughness (Ra) in high speed hard turning. An experimental investigation was conducted to predict the surface roughness in the finish hard turning with higher cutting speed. A set of sparse experimental data for finish turning of hardened steel (AISI 4340) and mixed ceramic inserts made up of aluminum oxide and titanium carbide were used as work piece and cutting tools materials. Four different models for the surface roughness were developed by using regression analysis and artificial neural network techniques. Two different techniques have been used in the regression analysis; Box Behnken Design (BBD) and Face Central Cubic Design (FCC).. The BBD model gave better prediction than the FCC in the design boundary Praise Worthy Prize 2014-03 Article PeerReviewed application/pdf en http://irep.iium.edu.my/36862/1/017-Al_Hazza_def_15204_-1.pdf application/pdf en http://irep.iium.edu.my/36862/4/36862_Surface%20roughness_scopus.pdf Al Hazza, Muataz Hazza Faizi and Adesta, Erry Yulian Triblas and Hassan, Muhammad Hasibul and Shaffiar, Norhashimah (2014) Surface roughness modeling in high speed hard turning using regression analysis. International Review of Mechanical Engineering, 8 (2). pp. 431-436. ISSN 1970-8734 http://www.praiseworthyprize.org/jsm/index.php?journal=ireme&page=article&op=view&path[]=15204
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	T Technology (General)
spellingShingle	T Technology (General) Al Hazza, Muataz Hazza Faizi Adesta, Erry Yulian Triblas Hassan, Muhammad Hasibul Shaffiar, Norhashimah Surface roughness modeling in high speed hard turning using regression analysis
description	Surface roughness plays an important role in the final quality of the machining parts. Therefore, predicting and simulating the roughness before the machining process is an important issue. The purpose of this research is to develop a reliable model for predicting and simulating the average surface roughness (Ra) in high speed hard turning. An experimental investigation was conducted to predict the surface roughness in the finish hard turning with higher cutting speed. A set of sparse experimental data for finish turning of hardened steel (AISI 4340) and mixed ceramic inserts made up of aluminum oxide and titanium carbide were used as work piece and cutting tools materials. Four different models for the surface roughness were developed by using regression analysis and artificial neural network techniques. Two different techniques have been used in the regression analysis; Box Behnken Design (BBD) and Face Central Cubic Design (FCC).. The BBD model gave better prediction than the FCC in the design boundary
format	Article
author	Al Hazza, Muataz Hazza Faizi Adesta, Erry Yulian Triblas Hassan, Muhammad Hasibul Shaffiar, Norhashimah
author_facet	Al Hazza, Muataz Hazza Faizi Adesta, Erry Yulian Triblas Hassan, Muhammad Hasibul Shaffiar, Norhashimah
author_sort	Al Hazza, Muataz Hazza Faizi
title	Surface roughness modeling in high speed hard turning using regression analysis
title_short	Surface roughness modeling in high speed hard turning using regression analysis
title_full	Surface roughness modeling in high speed hard turning using regression analysis
title_fullStr	Surface roughness modeling in high speed hard turning using regression analysis
title_full_unstemmed	Surface roughness modeling in high speed hard turning using regression analysis
title_sort	surface roughness modeling in high speed hard turning using regression analysis
publisher	Praise Worthy Prize
publishDate	2014
url	http://irep.iium.edu.my/36862/ http://irep.iium.edu.my/36862/ http://irep.iium.edu.my/36862/1/017-Al_Hazza_def_15204_-1.pdf http://irep.iium.edu.my/36862/4/36862_Surface%20roughness_scopus.pdf
first_indexed	2018-09-07T05:49:28Z
last_indexed	2018-09-07T05:49:28Z
_version_	1610926646825582592

Surface roughness modeling in high speed hard turning using regression analysis

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