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

Authors: G. Aswin Ramaswamy; Amal Krishna; M. Gautham; S.S. Sudharshan; J. Gokulachandran

Addresses: Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Tamil Nadu, India ' Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Tamil Nadu, India ' Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Tamil Nadu, India ' Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Tamil Nadu, India ' Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Tamil Nadu, India

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.

Keywords: optimisation; prediction; Taguchi method; artificial neural network; ANN; fuzzy logic.

DOI: 10.1504/IJPMB.2021.118323

International Journal of Process Management and Benchmarking, 2021 Vol.11 No.6, pp.864 - 890

Received: 25 Apr 2019
Accepted: 28 Sep 2019
Published online: 20 Oct 2021 *

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