Electrical Discharge Machining of Al (6351)-5% SiC-10% B4C Hybrid Composite: A Grey Relational Approach

Electrical Discharge Machining of Al (6351)-5% SiC-10% B4C Hybrid Composite: A Grey Relational Approach

The goal of the present experimental work is to optimize the electrical discharge machining (EDM) parameters of aluminum alloy (Al 6351) matrix reinforced with 5 wt.% silicon carbide (SiC) and 10 wt.% boron carbide (B4C) particles fabricated through the stir casting route. Multiresponse optimization...

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Main Authors: S. Suresh Kumar, M. Uthayakumar, S. Thirumalai Kumaran, P. Parameswaran, E. Mohandas
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Modelling and Simulation in Engineering
Online Access:http://dx.doi.org/10.1155/2014/426718
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spelling doaj-82f359d5beae420d9efca36f5be097402020-11-25T00:19:42ZengHindawi LimitedModelling and Simulation in Engineering1687-55911687-56052014-01-01201410.1155/2014/426718426718Electrical Discharge Machining of Al (6351)-5% SiC-10% B4C Hybrid Composite: A Grey Relational ApproachS. Suresh Kumar0M. Uthayakumar1S. Thirumalai Kumaran2P. Parameswaran3E. Mohandas4Department of Mechanical Engineering, Kalasalingam University, Krishnankoil 626126, IndiaDepartment of Mechanical Engineering, Kalasalingam University, Krishnankoil 626126, IndiaDepartment of Mechanical Engineering, Kalasalingam University, Krishnankoil 626126, IndiaPhysical Metallurgy Group, Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, IndiaPhysical Metallurgy Group, Indira Gandhi Centre for Atomic Research, Kalpakkam 603102, IndiaThe goal of the present experimental work is to optimize the electrical discharge machining (EDM) parameters of aluminum alloy (Al 6351) matrix reinforced with 5 wt.% silicon carbide (SiC) and 10 wt.% boron carbide (B4C) particles fabricated through the stir casting route. Multiresponse optimization was carried out through grey relational analysis (GRA) with an objective to minimize the machining characteristics, namely electrode wear ratio (EWR), surface roughness (SR) and power consumption (PC). The optimal combination of input parameters is identified, which shows the significant enhancement in process characteristics. Contributions of each machining parameter to the responses are calculated using analysis of variance (ANOVA). The result shows that the pulse current contributes more (83.94%) to affecting the combined output responses.http://dx.doi.org/10.1155/2014/426718
collection DOAJ
language English
format Article
sources DOAJ
author S. Suresh Kumar
M. Uthayakumar
S. Thirumalai Kumaran
P. Parameswaran
E. Mohandas
spellingShingle S. Suresh Kumar
M. Uthayakumar
S. Thirumalai Kumaran
P. Parameswaran
E. Mohandas
Electrical Discharge Machining of Al (6351)-5% SiC-10% B4C Hybrid Composite: A Grey Relational Approach
Modelling and Simulation in Engineering
author_facet S. Suresh Kumar
M. Uthayakumar
S. Thirumalai Kumaran
P. Parameswaran
E. Mohandas
author_sort S. Suresh Kumar
title Electrical Discharge Machining of Al (6351)-5% SiC-10% B4C Hybrid Composite: A Grey Relational Approach
title_short Electrical Discharge Machining of Al (6351)-5% SiC-10% B4C Hybrid Composite: A Grey Relational Approach
title_full Electrical Discharge Machining of Al (6351)-5% SiC-10% B4C Hybrid Composite: A Grey Relational Approach
title_fullStr Electrical Discharge Machining of Al (6351)-5% SiC-10% B4C Hybrid Composite: A Grey Relational Approach
title_full_unstemmed Electrical Discharge Machining of Al (6351)-5% SiC-10% B4C Hybrid Composite: A Grey Relational Approach
title_sort electrical discharge machining of al (6351)-5% sic-10% b4c hybrid composite: a grey relational approach
publisher Hindawi Limited
series Modelling and Simulation in Engineering
issn 1687-5591
1687-5605
publishDate 2014-01-01
description The goal of the present experimental work is to optimize the electrical discharge machining (EDM) parameters of aluminum alloy (Al 6351) matrix reinforced with 5 wt.% silicon carbide (SiC) and 10 wt.% boron carbide (B4C) particles fabricated through the stir casting route. Multiresponse optimization was carried out through grey relational analysis (GRA) with an objective to minimize the machining characteristics, namely electrode wear ratio (EWR), surface roughness (SR) and power consumption (PC). The optimal combination of input parameters is identified, which shows the significant enhancement in process characteristics. Contributions of each machining parameter to the responses are calculated using analysis of variance (ANOVA). The result shows that the pulse current contributes more (83.94%) to affecting the combined output responses.
url http://dx.doi.org/10.1155/2014/426718
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AT muthayakumar electricaldischargemachiningofal63515sic10b4chybridcompositeagreyrelationalapproach
AT sthirumalaikumaran electricaldischargemachiningofal63515sic10b4chybridcompositeagreyrelationalapproach
AT pparameswaran electricaldischargemachiningofal63515sic10b4chybridcompositeagreyrelationalapproach
AT emohandas electricaldischargemachiningofal63515sic10b4chybridcompositeagreyrelationalapproach
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