Predicting surface roughness with respect to process parameters using Regression Analysis Models in end milling

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

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Abstract

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).

Item Type:	Article (Journal)
Additional Information:	5515/29225
Uncontrolled Keywords:	surface roughness, RSM, end milling, H13
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering
Depositing User:	Dr Muataz Hazza Alhazza
Date Deposited:	27 Feb 2013 08:16
Last Modified:	30 May 2013 13:11
URI:	http://irep.iium.edu.my/id/eprint/29225

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