Multi-objective optimization of magnetic abrasive finishing by desirability function with genetic algorithm

Thermal stability and Surface hardness of the super-finished surface is a very important aspect to preserve texture workpiece in MAF process. In this present study, multi-objective optimization EN-31 finished through “Increase Temperature” Hardness” are considered for diminish their impact on EN-31. work Desirability function analysis (DFA) has been used optimize desired responses Experiments were designed according Taguchi L9 orthogonal array finishing The experiment results processed using DFA fitness established convert single response multi-response. Genetic Algorithm (GA) enhance regression model was developed obtain objective algorithm. Smaller-the-best criteria ‘Increase Temperature’ Hardness’ obtaining favorable process parameters. best optimal parametric combination obtained by GA-DFA hybrid approach at 2.5 mm (working gap), 20 gm (abrasive weight), 2.0 A (Current) 300 rpm (rotational speed).