Optimization of laser-assisted jet electrochemical machining parameters by grey relational analysis and fuzzy logic

Abstract

Purpose

The purpose of this paper is to optimize the laser-assisted jet electrochemical machining parameters, namely, supply voltage, inter-electrode gap, duty cycle and electrolyte concentration during machining of WC-Co composite using grey relational analysis and fuzzy logic.

Design/methodology/approach

In this work, experiments were carried out as per the Taguchi methodology and an L16 orthogonal array was used to study the influence of various combinations of process parameters on material removal rate, hole taper angle and surface roughness height. As a dynamic approach, the multiple response optimization was carried out using grey relational analysis and fuzzy logic.

Findings

The process parameters were optimized using grey relational analysis and fuzzy logic for different machining conditions such as balanced manufacturing, high-speed manufacturing and high-quality manufacturing. The research documented in this paper can be scaled up for case studies regarding industrial applications to compare optimization methods for manufacturing processes that are already being carried out.

Originality/value

An attempt to optimize material removal rate, hole taper angle and surface roughness height together by a combined approach of grey relational analysis and fuzzy logic has not been previously done.

Citation

Malik, A. and Sanghvi, N. (2022), "Optimization of laser-assisted jet electrochemical machining parameters by grey relational analysis and fuzzy logic", World Journal of Engineering, Vol. 19 No. 3, pp. 302-309. https://doi.org/10.1108/WJE-08-2020-0405