Parametric investigation of tool wear rate in EDM of Fe-based shape memory alloy: microstructural analysis and optimization using genetic algorithm

Abstract

Purpose

This study aims to experimentally investigate the influence of considered process parameters, i.e. pulse on time, pulse off time, peak current and gap voltage, on tool wear rate (TWR) in electrical discharge machining (EDM) of iron (Fe)-based shape memory alloy (SMA) through designed experiments. The parametric optimization for TWR has also been attempted using the desirability approach and genetic algorithm (GA).

Design/methodology/approach

The response surface methodology (RSM) in the form of Box–Behnken design has been used to scheme out the experiments. The influence of considered process inputs has also been observed through variance analysis. The reliability and fitness of the developed mathematical model have been established with test results. Microstructure analysis of machined samples has also been evaluated and analyzed using a scanning electron microscope (SEM). SEM images revealed the surface characteristics such as micro-cracks, craters and voids on the tool electrode surface. SEM images provide information about the surface integrity and type of wear on the surface of the tool electrode.

Findings

The input parameters, namely, pulse on time and pulse off time, are major influential factors impacting the TWR. High TWR has been reported at large pulse on time and small pulse off time conditions whereas higher TWR is reported at high peak current input settings. The maximum and minimum TWR values obtained are 0.073 g/min and 0.017 g/min, respectively. The optimization with desirability approach and GA reveals the best parametric values for TWR i.e. 0.01581 g/min and 0.00875 g/min at parametric combination as pulse on time = 60.83 µs, pulse off time = 112.16 µs, peak current = 18.64 A and gap voltage = 59.55 V, and pulse on time = 60 µs, pulse off time = 120 µs, peak current = 12 A and gap voltage = 40 V, correspondingly.

Research limitations/implications

Proposed work has no limitations.

Originality/value

SMAs have been well known for their superior and excellent properties, which make them an eligible candidate of paramount importance in real-life industrial applications such as orthopedic implants, actuators, micro tools, stents, coupling, sealing elements, aerospace components, defense instruments, manufacturing elements and bio-medical appliances. However, its effective and productive processing is still a challenge. Tool wear study while processing of SMAs in EDM process is an area which has been less investigated and of major concern for exploring the various properties of the tool and wear in it. Also, the developed mathematical model for TWR through the RSM approach will be helpful in industrial revelation.

Citation

Singh, R., Singh, R.P. and Trehan, R. (2022), "Parametric investigation of tool wear rate in EDM of Fe-based shape memory alloy: microstructural analysis and optimization using genetic algorithm", World Journal of Engineering, Vol. 19 No. 3, pp. 418-428. https://doi.org/10.1108/WJE-04-2021-0203