Optimization of Machining Parameters for Minimum Surface Roughness in Turning of Aluminium- Magnesium Alloy Using a 0.4 mm Nose Radius Tool: A Taguchi Approach

Abstract

This study presents a systematic investigation to optimize the turning parameters in order to minimize surface roughness (Ra) of an Aluminum–Magnesium alloy (Al3Mg) using a CNC turning machine and a cutting tool insert with a 0.4 mm nose radius. The work employs the Taguchi Design of Experiments (DOE) methodology to analyze the effects of three main control factors (cutting speed, feed rate, and depth of cut), each at three levels. An L9 orthogonal array was used to design the experiments. In this study, the “smaller-the-better” signal-to-noise (S/N) ratio was utilized as the performance metric to evaluate surface roughness. Analysis of Variance (ANOVA) was performed to determine the statistical significance and percentage contribution of the turning parameters. The optimal parameter combination for the 0.4 mm nose radius tool was: Cutting Speed (B3) = 900 rpm, Feed Rate (A1) = 0.3 mm/rev, and Depth of Cut (C2) = 1.0 mm. The ANOVA results indicated that feed rate was the most significant contributing factor, accounting for 88.97% of the total variation in surface roughness, followed by cutting speed (4.44%) and depth of cut (3.14%). The predicted surface roughness under optimal conditions was 508.21 µm. This study demonstrates the effectiveness of the Taguchi methodology for process optimization, leading to improved surface roughness with a minimal number of experiments.