Analyzing the influence of electrical parameters on EDM process of Ti6Al4V alloy using Adaptive Neuro-fuzzy Inference System (ANFIS)

Electrical discharge machining (EDM) is machining process that is suitable for machining very hard materials that are electrically conductive. In this process the material is removed by series of repeated electrical discharges, produced by electric pulse generators at short intervals in dielectric...

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Main Authors:	Al Hazza, Muataz Hazza Faizi, Mohammed, Baba Ndaliman, Mohammad, Yeakub Ali, Khan, Ahsan Ali
Format:	Article
Language:	English English
Published:	Praise Worthy Prize 2015
Subjects:	TS200 Metal manufactures. Metalworking
Online Access:	http://irep.iium.edu.my/43939/ http://irep.iium.edu.my/43939/ http://irep.iium.edu.my/43939/1/Baba_2015-1.pdf http://irep.iium.edu.my/43939/4/43939_Analyzing%20the%20influence%20of%20electrical%20parameters%20on%20EDM%20process%20of%20Ti6Al4V_SCOPUS.pdf

id	iium-43939
recordtype	eprints
spelling	iium-439392017-11-07T07:45:03Z http://irep.iium.edu.my/43939/ Analyzing the influence of electrical parameters on EDM process of Ti6Al4V alloy using Adaptive Neuro-fuzzy Inference System (ANFIS) Al Hazza, Muataz Hazza Faizi Mohammed, Baba Ndaliman Mohammad, Yeakub Ali Khan, Ahsan Ali TS200 Metal manufactures. Metalworking Electrical discharge machining (EDM) is machining process that is suitable for machining very hard materials that are electrically conductive. In this process the material is removed by series of repeated electrical discharges, produced by electric pulse generators at short intervals in dielectric fluid medium. Thus, the electrical parameters are the main process parameters. However, the complexity of this cutting process will not permit pure analytical physical investigating. Therefore, the conventional mathematical models may not be suitable for analysing the output responses. The aim of this research is to investigate and predict the influence of the electrical parameters: peak current (PC), pulse duration (PD) and duty factor (DF) on the surface roughness (SR), Material Removal Rate (MRR) and Tool Wear Rate (TWR) using Adaptive Neuro-Fuzzy Inference System (ANFIS) as one of the effective soft computing methods. In this research, a set of experimental data was obtained with different levels. The measured values have been used to train the ANFIS system to find minimum error. The results indicate that even with the complexity of the EDM process, the Adaptive Neuro-Fuzzy Inference System (ANFIS) was found to be adequate in predicting the SR, MRR and TWR with high accuracy. Praise Worthy Prize 2015-05 Article PeerReviewed application/pdf en http://irep.iium.edu.my/43939/1/Baba_2015-1.pdf application/pdf en http://irep.iium.edu.my/43939/4/43939_Analyzing%20the%20influence%20of%20electrical%20parameters%20on%20EDM%20process%20of%20Ti6Al4V_SCOPUS.pdf Al Hazza, Muataz Hazza Faizi and Mohammed, Baba Ndaliman and Mohammad, Yeakub Ali and Khan, Ahsan Ali (2015) Analyzing the influence of electrical parameters on EDM process of Ti6Al4V alloy using Adaptive Neuro-fuzzy Inference System (ANFIS). International Review of Mechanical Engineering, 9 (3). pp. 237-241. ISSN 1970-8734 http://www.praiseworthyprize.org/jsm/index.php?journal=ireme&page=article&op=view&path%5B%5D=17179
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 Al Hazza, Muataz Hazza Faizi Mohammed, Baba Ndaliman Mohammad, Yeakub Ali Khan, Ahsan Ali Analyzing the influence of electrical parameters on EDM process of Ti6Al4V alloy using Adaptive Neuro-fuzzy Inference System (ANFIS)
description	Electrical discharge machining (EDM) is machining process that is suitable for machining very hard materials that are electrically conductive. In this process the material is removed by series of repeated electrical discharges, produced by electric pulse generators at short intervals in dielectric fluid medium. Thus, the electrical parameters are the main process parameters. However, the complexity of this cutting process will not permit pure analytical physical investigating. Therefore, the conventional mathematical models may not be suitable for analysing the output responses. The aim of this research is to investigate and predict the influence of the electrical parameters: peak current (PC), pulse duration (PD) and duty factor (DF) on the surface roughness (SR), Material Removal Rate (MRR) and Tool Wear Rate (TWR) using Adaptive Neuro-Fuzzy Inference System (ANFIS) as one of the effective soft computing methods. In this research, a set of experimental data was obtained with different levels. The measured values have been used to train the ANFIS system to find minimum error. The results indicate that even with the complexity of the EDM process, the Adaptive Neuro-Fuzzy Inference System (ANFIS) was found to be adequate in predicting the SR, MRR and TWR with high accuracy.
format	Article
author	Al Hazza, Muataz Hazza Faizi Mohammed, Baba Ndaliman Mohammad, Yeakub Ali Khan, Ahsan Ali
author_facet	Al Hazza, Muataz Hazza Faizi Mohammed, Baba Ndaliman Mohammad, Yeakub Ali Khan, Ahsan Ali
author_sort	Al Hazza, Muataz Hazza Faizi
title	Analyzing the influence of electrical parameters on EDM process of Ti6Al4V alloy using Adaptive Neuro-fuzzy Inference System (ANFIS)
title_short	Analyzing the influence of electrical parameters on EDM process of Ti6Al4V alloy using Adaptive Neuro-fuzzy Inference System (ANFIS)
title_full	Analyzing the influence of electrical parameters on EDM process of Ti6Al4V alloy using Adaptive Neuro-fuzzy Inference System (ANFIS)
title_fullStr	Analyzing the influence of electrical parameters on EDM process of Ti6Al4V alloy using Adaptive Neuro-fuzzy Inference System (ANFIS)
title_full_unstemmed	Analyzing the influence of electrical parameters on EDM process of Ti6Al4V alloy using Adaptive Neuro-fuzzy Inference System (ANFIS)
title_sort	analyzing the influence of electrical parameters on edm process of ti6al4v alloy using adaptive neuro-fuzzy inference system (anfis)
publisher	Praise Worthy Prize
publishDate	2015
url	http://irep.iium.edu.my/43939/ http://irep.iium.edu.my/43939/ http://irep.iium.edu.my/43939/1/Baba_2015-1.pdf http://irep.iium.edu.my/43939/4/43939_Analyzing%20the%20influence%20of%20electrical%20parameters%20on%20EDM%20process%20of%20Ti6Al4V_SCOPUS.pdf
first_indexed	2023-09-18T21:02:31Z
last_indexed	2023-09-18T21:02:31Z
_version_	1777410717940449280

Analyzing the influence of electrical parameters on EDM process of Ti6Al4V alloy using Adaptive Neuro-fuzzy Inference System (ANFIS)

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