Experimental modeling techniques in electrical discharge machining (EDM): a review

Electrical discharge machining (EDM) is a widely used non-conventional machining technique in manufacturing industries, capable of accurately machining electrically conductive materials of any hardness and strength. However, to achieve low production costs and minimal machining time, a comprehensi...

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Main Authors: Hasan, Mohammad Mainul, Saleh, Tanveer, Sophian, Ali, Rahman, M. Azizur, Huang, Tao, Mohamed Ali, Mohamed Sultan
Format: Article
Language:English
English
Published: Springer Nature 2023
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Online Access:http://irep.iium.edu.my/105168/13/105168_Experimental%20modeling%20techniques.pdf
http://irep.iium.edu.my/105168/14/105168_Experimental%20modeling%20techniques_Scopus.pdf
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https://link.springer.com/article/10.1007/s00170-023-11603-x
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Institution: Universiti Islam Antarabangsa Malaysia
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spelling my.iium.irep.1051682024-05-17T07:14:06Z http://irep.iium.edu.my/105168/ Experimental modeling techniques in electrical discharge machining (EDM): a review Hasan, Mohammad Mainul Saleh, Tanveer Sophian, Ali Rahman, M. Azizur Huang, Tao Mohamed Ali, Mohamed Sultan T Technology (General) Electrical discharge machining (EDM) is a widely used non-conventional machining technique in manufacturing industries, capable of accurately machining electrically conductive materials of any hardness and strength. However, to achieve low production costs and minimal machining time, a comprehensive understanding of the EDM system is necessary. Due to the stochastic nature of the process and the numerous variables involved, it can be challenging to develop an analytical model of EDM through theoretical and numerical simulations alone. This paper conducts an extensive review of the various experimental (or empirical) modeling techniques used by researchers over the past two decades, including a geographic and temporal analysis of these approaches. The major methods employed to describe the EDM process include regression, response surface methodology (RSM), fuzzy inference systems (FIS), artificial neural networks (ANN), and adaptive neuro-fuzzy inference systems (ANFIS). Additionally, the optimization methods used in conjunction with these methods are also discussed. Although RSM is the most commonly used empirical modeling technique, recent years have seen an increase in the use of ANN for providing the most accurate predictions of EDM process responses. The review of the literature shows that most of the investigations on experimental EDM modeling were conducted in Asia. Springer Nature 2023-06-06 Article PeerReviewed application/pdf en http://irep.iium.edu.my/105168/13/105168_Experimental%20modeling%20techniques.pdf application/pdf en http://irep.iium.edu.my/105168/14/105168_Experimental%20modeling%20techniques_Scopus.pdf Hasan, Mohammad Mainul and Saleh, Tanveer and Sophian, Ali and Rahman, M. Azizur and Huang, Tao and Mohamed Ali, Mohamed Sultan (2023) Experimental modeling techniques in electrical discharge machining (EDM): a review. International Journal of Advanced Manufacturing Technology, 127 (5-6). pp. 2125-2150. ISSN 0268-3768 E-ISSN 1433-3015 https://link.springer.com/article/10.1007/s00170-023-11603-x 10.1007/s00170-023-11603-x
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic T Technology (General)
spellingShingle T Technology (General)
Hasan, Mohammad Mainul
Saleh, Tanveer
Sophian, Ali
Rahman, M. Azizur
Huang, Tao
Mohamed Ali, Mohamed Sultan
Experimental modeling techniques in electrical discharge machining (EDM): a review
description Electrical discharge machining (EDM) is a widely used non-conventional machining technique in manufacturing industries, capable of accurately machining electrically conductive materials of any hardness and strength. However, to achieve low production costs and minimal machining time, a comprehensive understanding of the EDM system is necessary. Due to the stochastic nature of the process and the numerous variables involved, it can be challenging to develop an analytical model of EDM through theoretical and numerical simulations alone. This paper conducts an extensive review of the various experimental (or empirical) modeling techniques used by researchers over the past two decades, including a geographic and temporal analysis of these approaches. The major methods employed to describe the EDM process include regression, response surface methodology (RSM), fuzzy inference systems (FIS), artificial neural networks (ANN), and adaptive neuro-fuzzy inference systems (ANFIS). Additionally, the optimization methods used in conjunction with these methods are also discussed. Although RSM is the most commonly used empirical modeling technique, recent years have seen an increase in the use of ANN for providing the most accurate predictions of EDM process responses. The review of the literature shows that most of the investigations on experimental EDM modeling were conducted in Asia.
format Article
author Hasan, Mohammad Mainul
Saleh, Tanveer
Sophian, Ali
Rahman, M. Azizur
Huang, Tao
Mohamed Ali, Mohamed Sultan
author_facet Hasan, Mohammad Mainul
Saleh, Tanveer
Sophian, Ali
Rahman, M. Azizur
Huang, Tao
Mohamed Ali, Mohamed Sultan
author_sort Hasan, Mohammad Mainul
title Experimental modeling techniques in electrical discharge machining (EDM): a review
title_short Experimental modeling techniques in electrical discharge machining (EDM): a review
title_full Experimental modeling techniques in electrical discharge machining (EDM): a review
title_fullStr Experimental modeling techniques in electrical discharge machining (EDM): a review
title_full_unstemmed Experimental modeling techniques in electrical discharge machining (EDM): a review
title_sort experimental modeling techniques in electrical discharge machining (edm): a review
publisher Springer Nature
publishDate 2023
url http://irep.iium.edu.my/105168/13/105168_Experimental%20modeling%20techniques.pdf
http://irep.iium.edu.my/105168/14/105168_Experimental%20modeling%20techniques_Scopus.pdf
http://irep.iium.edu.my/105168/
https://link.springer.com/article/10.1007/s00170-023-11603-x
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