Modeling and multi-objective optimization of powder mixed electric discharge machining process of aluminum/alumina metal matrix composite

Low material removal rate (MRR) and high surface roughness values hinder large-scale application of electro discharge machining (EDM) in the fields like automobile, aerospace and medical industry. In recent years, however, EDM has gained more significance in these industries as the usage of difficul...

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Main Authors: Gangadharudu Talla, Deepak Kumar Sahoo, S. Gangopadhyay, C.K. Biswas
Format: Article
Language:English
Published: Elsevier 2015-09-01
Series:Engineering Science and Technology, an International Journal
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2215098615000270
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spelling doaj-8491697f51e1464292e112c559e1276e2020-11-25T01:00:40ZengElsevierEngineering Science and Technology, an International Journal2215-09862015-09-0118336937310.1016/j.jestch.2015.01.007Modeling and multi-objective optimization of powder mixed electric discharge machining process of aluminum/alumina metal matrix compositeGangadharudu Talla0Deepak Kumar Sahoo1S. Gangopadhyay2C.K. Biswas3Department of Mechanical Engineering, National Institute of Technology, Rourkela 769008, IndiaDepartment of Mechanical Engineering, National Institute of Technology, Rourkela 769008, IndiaDepartment of Mechanical Engineering, National Institute of Technology, Rourkela 769008, IndiaDepartment of Petroleum Engineering, Universiti Teknologi Petronas, Ipoh, MalaysiaLow material removal rate (MRR) and high surface roughness values hinder large-scale application of electro discharge machining (EDM) in the fields like automobile, aerospace and medical industry. In recent years, however, EDM has gained more significance in these industries as the usage of difficult-to-machine materials including metal matrix composites (MMCs) increased. In the present work, an attempt has been made to fabricate and machine aluminum/alumina MMC using EDM by adding aluminum powder in kerosene dielectric. Results showed an increase in MRR and decrease in surface roughness (Ra) compared to those for conventional EDM. Semi empirical models for MRR and Ra based on machining parameters and important thermo physical properties were established using a hybrid approach of dimensional and regression analysis. A multi response optimization was also performed using principal component analysis-based grey technique (Grey-PCA) to determine optimum settings of process parameters for maximum MRR and minimum Ra within the experimental range. The recommended setting of process parameters for the proposed process has been found to be powder concentration (Cp) = 4 g/l, peak current (Ip) = 3 A, pulse on time (Ton) = 150 μs and duty cycle (Tau) = 85%.http://www.sciencedirect.com/science/article/pii/S2215098615000270Dimensional analysisGrey-PCAMetal matrix compositeModelingMulti-objective optimizationPowder mixed electric discharge machining
collection DOAJ
language English
format Article
sources DOAJ
author Gangadharudu Talla
Deepak Kumar Sahoo
S. Gangopadhyay
C.K. Biswas
spellingShingle Gangadharudu Talla
Deepak Kumar Sahoo
S. Gangopadhyay
C.K. Biswas
Modeling and multi-objective optimization of powder mixed electric discharge machining process of aluminum/alumina metal matrix composite
Engineering Science and Technology, an International Journal
Dimensional analysis
Grey-PCA
Metal matrix composite
Modeling
Multi-objective optimization
Powder mixed electric discharge machining
author_facet Gangadharudu Talla
Deepak Kumar Sahoo
S. Gangopadhyay
C.K. Biswas
author_sort Gangadharudu Talla
title Modeling and multi-objective optimization of powder mixed electric discharge machining process of aluminum/alumina metal matrix composite
title_short Modeling and multi-objective optimization of powder mixed electric discharge machining process of aluminum/alumina metal matrix composite
title_full Modeling and multi-objective optimization of powder mixed electric discharge machining process of aluminum/alumina metal matrix composite
title_fullStr Modeling and multi-objective optimization of powder mixed electric discharge machining process of aluminum/alumina metal matrix composite
title_full_unstemmed Modeling and multi-objective optimization of powder mixed electric discharge machining process of aluminum/alumina metal matrix composite
title_sort modeling and multi-objective optimization of powder mixed electric discharge machining process of aluminum/alumina metal matrix composite
publisher Elsevier
series Engineering Science and Technology, an International Journal
issn 2215-0986
publishDate 2015-09-01
description Low material removal rate (MRR) and high surface roughness values hinder large-scale application of electro discharge machining (EDM) in the fields like automobile, aerospace and medical industry. In recent years, however, EDM has gained more significance in these industries as the usage of difficult-to-machine materials including metal matrix composites (MMCs) increased. In the present work, an attempt has been made to fabricate and machine aluminum/alumina MMC using EDM by adding aluminum powder in kerosene dielectric. Results showed an increase in MRR and decrease in surface roughness (Ra) compared to those for conventional EDM. Semi empirical models for MRR and Ra based on machining parameters and important thermo physical properties were established using a hybrid approach of dimensional and regression analysis. A multi response optimization was also performed using principal component analysis-based grey technique (Grey-PCA) to determine optimum settings of process parameters for maximum MRR and minimum Ra within the experimental range. The recommended setting of process parameters for the proposed process has been found to be powder concentration (Cp) = 4 g/l, peak current (Ip) = 3 A, pulse on time (Ton) = 150 μs and duty cycle (Tau) = 85%.
topic Dimensional analysis
Grey-PCA
Metal matrix composite
Modeling
Multi-objective optimization
Powder mixed electric discharge machining
url http://www.sciencedirect.com/science/article/pii/S2215098615000270
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