Optimization of Cutting Parameters in Machining GFRP Using End Mill Cutter through DoE and Verification through Genetic Algorithm

Abstract

This article discusses optimization of critical parameters such as cutting speed, feed, depth of cut and method of machining while machining Glass Fiber Reinforced Plastic (GFRP) in vertical machining center using standard end mill cutter made up of High Speed Steel (HSS) for lesser cutting load, maximum material removal rate for better surface finish and dimensional accuracy through design of experiments. In composite material machining, surface finish is the critical deciding factor in determining surface quality. In this study, as per Taguchi’s L9 orthogonal array, predictable and unpredictable parts are followed to evaluate the consequence of cutting parameters on the machined component. The study includes surface roughness measurement using surface profilometer continued by physical measurement of machined pocket dimension. The experimental results, suggest suitable machining parameters in order to achieve the above target goal. In addition, C++ program is developed to cross check the most favorable machining parameters for maximum material removal rate using genetic algorithm. It is inferred from the study that the genetic algorithm results coincides very closely with the result given by the method of design of experiments.