Modeling the effect of CNT concentration in dielectric fluid on EDM performance using neural network

Electrical discharge machining (EDM) is one of the most reliable and precise manufacturing processes that applicable for creating complex geometries. However, the high heat produce on the electrically discharged material during the EDM process will minimize the surface quality of final product. Carb...

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Main Authors:	Khan, Ahsan Ali, Al Hazza, Muataz Hazza Faizi, Adesta, Erry Yulian Triblas, Mohd. Fauzey, Nur Fadhilah
Format:	Conference or Workshop Item
Language:	English English
Published:	The Institute of Electrical and Electronics Engineers, Inc. 2016
Subjects:	TS200 Metal manufactures. Metalworking
Online Access:	http://irep.iium.edu.my/47432/ http://irep.iium.edu.my/47432/ http://irep.iium.edu.my/47432/ http://irep.iium.edu.my/47432/1/47432_modeling_the_effect_of_CNT.pdf http://irep.iium.edu.my/47432/4/47432_Modeling%20the%20Effect_Scopus.pdf

id	iium-47432
recordtype	eprints
spelling	iium-474322016-12-20T04:02:47Z http://irep.iium.edu.my/47432/ Modeling the effect of CNT concentration in dielectric fluid on EDM performance using neural network Khan, Ahsan Ali Al Hazza, Muataz Hazza Faizi Adesta, Erry Yulian Triblas Mohd. Fauzey, Nur Fadhilah TS200 Metal manufactures. Metalworking Electrical discharge machining (EDM) is one of the most reliable and precise manufacturing processes that applicable for creating complex geometries. However, the high heat produce on the electrically discharged material during the EDM process will minimize the surface quality of final product. Carbon nanotubes possess unexpected strength and unique electrical and thermal properties. On the account of this, multi-wall carbon nanotubes (MWCNTs) are added to the dielectric used in the EDM process to improve its performance when machining the stainless steel using copper electrodes. In this research the effect of the concentration of MWCNTs and the peak current on the surface quality of stainless steel was investigated. The experimental result gained proved that addition of MWCNTs reduce the surface roughness and increase the material removal rate of work material. Due the number of experiment, the experiments have been simulated using JMP simulator with 500 run using the real results. The simulation results have been used in next step to develop the neural network model. The validation between the predicted and the simulation reseals show a high accuracy. The Institute of Electrical and Electronics Engineers, Inc. 2016 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/47432/1/47432_modeling_the_effect_of_CNT.pdf application/pdf en http://irep.iium.edu.my/47432/4/47432_Modeling%20the%20Effect_Scopus.pdf Khan, Ahsan Ali and Al Hazza, Muataz Hazza Faizi and Adesta, Erry Yulian Triblas and Mohd. Fauzey, Nur Fadhilah (2016) Modeling the effect of CNT concentration in dielectric fluid on EDM performance using neural network. In: 2015 4th International Conference on Advanced Computer Science Applications and Technologies (ACSAT 2015), 8th-10th Dec. 2015, Kuala Lumpur. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7478756 10.1109/ACSAT.2015.24
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	TS200 Metal manufactures. Metalworking
spellingShingle	TS200 Metal manufactures. Metalworking Khan, Ahsan Ali Al Hazza, Muataz Hazza Faizi Adesta, Erry Yulian Triblas Mohd. Fauzey, Nur Fadhilah Modeling the effect of CNT concentration in dielectric fluid on EDM performance using neural network
description	Electrical discharge machining (EDM) is one of the most reliable and precise manufacturing processes that applicable for creating complex geometries. However, the high heat produce on the electrically discharged material during the EDM process will minimize the surface quality of final product. Carbon nanotubes possess unexpected strength and unique electrical and thermal properties. On the account of this, multi-wall carbon nanotubes (MWCNTs) are added to the dielectric used in the EDM process to improve its performance when machining the stainless steel using copper electrodes. In this research the effect of the concentration of MWCNTs and the peak current on the surface quality of stainless steel was investigated. The experimental result gained proved that addition of MWCNTs reduce the surface roughness and increase the material removal rate of work material. Due the number of experiment, the experiments have been simulated using JMP simulator with 500 run using the real results. The simulation results have been used in next step to develop the neural network model. The validation between the predicted and the simulation reseals show a high accuracy.
format	Conference or Workshop Item
author	Khan, Ahsan Ali Al Hazza, Muataz Hazza Faizi Adesta, Erry Yulian Triblas Mohd. Fauzey, Nur Fadhilah
author_facet	Khan, Ahsan Ali Al Hazza, Muataz Hazza Faizi Adesta, Erry Yulian Triblas Mohd. Fauzey, Nur Fadhilah
author_sort	Khan, Ahsan Ali
title	Modeling the effect of CNT concentration in dielectric fluid on EDM performance using neural network
title_short	Modeling the effect of CNT concentration in dielectric fluid on EDM performance using neural network
title_full	Modeling the effect of CNT concentration in dielectric fluid on EDM performance using neural network
title_fullStr	Modeling the effect of CNT concentration in dielectric fluid on EDM performance using neural network
title_full_unstemmed	Modeling the effect of CNT concentration in dielectric fluid on EDM performance using neural network
title_sort	modeling the effect of cnt concentration in dielectric fluid on edm performance using neural network
publisher	The Institute of Electrical and Electronics Engineers, Inc.
publishDate	2016
url	http://irep.iium.edu.my/47432/ http://irep.iium.edu.my/47432/ http://irep.iium.edu.my/47432/ http://irep.iium.edu.my/47432/1/47432_modeling_the_effect_of_CNT.pdf http://irep.iium.edu.my/47432/4/47432_Modeling%20the%20Effect_Scopus.pdf
first_indexed	2023-09-18T21:07:30Z
last_indexed	2023-09-18T21:07:30Z
_version_	1777411031487741952

Modeling the effect of CNT concentration in dielectric fluid on EDM performance using neural network

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