Optimization of multi-response characteristics in CNC turning of Inconel 625 using Taguchi-grey relational analysis, weighted grey relational analysis, and analysis of variance methods

In experimental design, the classical Taguchi method is often used to improve the processes that have only one main outcome.However, in real manufacturing, particularly during machining, it is often necessary to consider several important characteristics simultaneously.This study used a combination of the Taguchi method and grey relational analysis (GRA) to improve the CNC dry turning of Inconel 625.The goal was to make the process more efficient while also ensuring better surface quality, which are two goals that often work against each other.The approach uses the data from Taguchi designs to calculate signal-to-noise ratios (S/N) and combines them with GRA to create a single measure of overall performance.To understand how each process setting affects the final result, an analysis of variance (ANOVA) is performed.The best settings found were a depth of cut of 1.0 mm, a cutting speed of 80 m/min, and a feed rate of 0.08 mm/rev.These settings give the best balance between removing material quickly and keeping the surface smooth.The tests done to examine these results confirmed that the method works well, with the actual results matching the expected outcomes closely.