Multi-performance optimization in wire EDM of Inconel 617 using GRA and genetic algorithm

Inconel 617 superalloy is a candidate material for various high temperature components employed in ultra-supercritical power plants. Superalloys are hard to machine materials that easier to process using nontraditional methods such as wire electrical discharge machining. This paper discusses multi perfor-mance optimization in machining of Inconel 617 using grey relational analysis and genetic algorithm. The performance characteristics of wire cut EDM are surface roughness, material removal rate, wire wear rate, form and orientation tolerances. Parameters under consideration are pulse on time, pulse off time, current, voltage, flushing pressure, wire tension, table feed and wire speed. The performance measures are consolidated as three performance indices using the grey relational grade. The mathematical models to estimate the performance objectives are developed using regression analysis. Multiobjective optimiza-tion is applied through genetic algorithm and a pareto front containing the optimized responses is com-puted. The optimized parameters are validated experimentally and the results are reported. Copyright (c) 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the 2nd International Con-ference on Functional Material, Manufacturing and Performances