Optimizing the five magnetic abrasive finishing factors on surface quality using Taguchi-based grey relational analysis

Abstract

The effectiveness of the magnetic abrasive finishing (MAF) process relies on several factors, including the brush’s flexibility that varies across tools. This study aimed to optimize the results of five key parameters (voltage, finishing time, gap distance, rotating speed, and particle size) on surface roughness (SR) and microhardness (HV) using the grey relational analysis (GRA) method. Experimental work employed the Taguchi design with L27 trials in Minitab 17, involving five variables with three levels for each. The impact of these parameters on microhardness and surface roughness for stainless steel SUS420 bubble cups was assessed using Taguchi and regression analyses. The best roughness improvement and the most substantial enhancement in microhardness were individually obtained with the GRA method. This method assigned the best results for both surface roughness and microhardness. According to Taguchi analysis, the voltage parameter has the main or maximum parameter effect on grade, followed by gap distance, time, spindle speed, and particle size. It was found that the optimal parameters were the same as the input parameters.