Implementation of the Taguchi Method for Optimizing Surface Roughness in the Aluminum Drilling Process

Abstract

Drilling is one of the important machining processes in the manufacturing industry, especially for lightweight materials such as aluminum. However, drilling aluminum poses significant challenges, including the generation of surface roughness and elevated temperatures in the cutting zone, which can accelerate tool wear. This study aims to optimize drilling parameters for aluminum under Minimum Quantity Lubrication (MQL) conditions, with surface roughness selected as the primary quality characteristic, where lower values indicate better performance. The investigated process parameters include spindle speed, feed rate, and type of cutting fluid. The experiments were designed using the Taguchi method with an L18 orthogonal array. Data were analyzed through signal-to-noise (S/N) ratio and analysis of variance (ANOVA) to identify the influence of each parameter. The results indicated that feed had the most significant effect on surface roughness, followed by spindle speed and the type of cutting fluid. The optimal combination of parameters, which includes a feed rate of 0.05 mm/rev, a spindle speed of 1500 rpm, and sunflower oil as the cutting fluid, yielded the lowest surface roughness and demonstrated the effectiveness of the Taguchi method in improving machining performance in aluminum drilling processes.