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Optimisation and prediction of machining parameters in EDM for Al-ZrO2 using soft computing techniques with Taguchi method

Publication Type : Journal Article

Publisher : Inderscience Publishers

Source : International Journal of Process Management and Benchmarking

Url : https://doi.org/10.1504/ijpmb.2021.118323

Campus : Coimbatore

School : School of Engineering

Department : Mechanical Engineering

Year : 2021

Abstract : In recent years, the usage of metal matrix composites has drastically increased in various engineering fields and hence the necessity for greater accuracy in machining of composites has also increased greatly. This study determines the optimal machining parameters viz., discharge current, pulse on time and voltage with respect to output performance such as material removal rate (MRR) and electrode wear rate (EWR) using electric discharge machine (EDM). Taguchi method is used for conducting experiments. Soft computing models such as artificial neural network (ANN) and fuzzy are developed to predict the process parameters. The developed models are validated with the experimental results. The results of both the models are also compared.

Cite this Research Publication : G. Aswin Ramaswamy, Amal Krishna, M. Gautham, S.S. Sudharshan, J. Gokulachandran, Optimisation and prediction of machining parameters in EDM for Al-ZrO2 using soft computing techniques with Taguchi method, International Journal of Process Management and Benchmarking, Inderscience Publishers, 2021, https://doi.org/10.1504/ijpmb.2021.118323

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