Effects of machining parameters on enhancing Alpha-Beta Titanium alloy using Taguchi-grey relational analysis for aerospace applications

Abstract

The need for enhancement of productivity and quality of the machined titanium alloy components is paramount to meet the high demands of aerospace parts. Various optimization techniques are being used widely to find suitable machining parameters to improve productivity and reduce surface defects. The present study aims to derive an optimal combination of process parameters during the end milling operation of Ti-6Al-4V alloy for enhancing performance measures which are surface roughness, specific cutting energy and material removal rate (MRR). The Grey relational optimization techniques along with Taguchi method has been utilized for finding the optimum machining parameters. It has been found that the axial depth of cut has the most significant factor on machining characteristics in end milling process of titanium alloy. Using Taguchi-Grey relational analysis technique, optimal process parameter combination has been computed and the performance enhancement using the optimal process combination has been verified by the confirmation test

A novel hybrid multi-criteria optimization of 3D printing process using grey relational analysis (GRA) coupled with principal component analysis (PCA)

“…[ analysis (GRA) and principal component analysis (PCA). The methodology consists of several well-defined steps [42][43][44][45][46], outlined below:…”