Development of Hybrid Optimization for Drilling Performance in Magnesium Alloy AM60 Using Biodegradable MQL and Taguchi– MA

ABSTRACT

This study investigates the influence of drilling input parameters—spindle speed, feed rate, depth of cut, and Minimum Quantity Lubrication (MQL) type—on the machining performance of magnesium alloy AM60, with a focus on enhancing key metrics such as Material Removal Rate (MRR), Surface Finish (SF), Tool Wear (TW), Hole Quality (HQ), Cylindricity, and Roundness while promoting sustainable practices using biodegradable lubricants. The study employs a Taguchi L9 orthogonal array for experimental design, testing three levels each of spindle speed (1500, 2000, 2500 rpm), feed rate (0.1, 0.125, 0.15 mm/min), and depth of cut (0.75, 1, 1.25 mm), along with three lubrication types (semi‐synthetic, biodegradable, synthetic). A hybrid optimization approach combining Robust Taguchi Experimental Design (RTED), Analysis of Variance (ANOVA), and the Multiattributive Border Approximation Area Comparison (MABAC) method is utilized for multiresponse optimization. The results demonstrate that biodegradable MQL achieves the best overall performance with an MRR of 2.5 cm ³ /min, SF of 1.2 μm, TW of 3.8 μm, HQ of 94 μm, cylindricity of 12 μm, and roundness of 8 μm under optimized conditions. ANOVA results confirm the statistical significance of MQL type on MRR. The study is limited to magnesium alloy AM60, and further research should explore different materials, machining environments, and tool geometries. The findings offer practical insights for industries such as aerospace and automotive, emphasizing the benefits of biodegradable lubricants in precision drilling operations. This research integrates Taguchi ANOVA and the MABAC method for the first time in a multiresponse optimization approach, combined with eco‐friendly lubrication strategies, contributing to sustainable manufacturing practices.