Enhancing Machining Performance: A Study on Taguchi ANOVA and Grey Relational Analysis

This study aims to optimize surface roughness (Ra) and material removal rate (MRR) in machining processes by analyzing the effects of cutting parameters: speed, feed rate, and depth of cut. The primary objectives include identifying optimal parameter settings to minimize Ra and maximize MRR, and understanding the relative significance of each parameter. The study's hypotheses propose that variations in speed, feed rate, and depth of cut significantly influence Ra and MRR, with feed rate expected to have the greatest impact. The methodology involves conducting 27 experimental runs based on a Taguchi L27 orthogonal array. Surface roughness and MRR were measured for each run, and corresponding signal-to-noise (S/N) ratios were calculated using the "lower is better" criterion for Ra and the "larger is better" criterion for MRR. Analysis of variance (ANOVA) was performed to determine the significance and contribution of each factor. For surface roughness (Ra), the smallest value was 0.58 micrometers with an S/N ratio of 4.7314, while the highest value was 1.86 micrometers with an S/N ratio of -5.3903. Regarding the material removal rate (MRR), the highest value recorded was 8007.751 mm³/min with an S/N ratio of 78.07021, and the lowest was 1113.927 mm³/min with an S/N ratio of 60.93713. ANOVA analysis revealed the statistical significance of each factor and its interactions, highlighting the critical parameters for process optimization. Additionally, the Grey Relational Analysis (GRA) was utilized to refine the selection and prioritization between minimizing surface roughness and maximizing the material removal rate. Furthermore, to strike a balance between surface finish and material removal rate, it is recommended to consider higher feed rates and depth of cut, along with lower cutting speeds. Future studies should explore additional factors, such as tool wear and material properties to enhance machining performance. Keywords: Machining Optimization, Experimental Design, Taguchi Method, ANOVA Analysis, Grey Relational Analysis (GRA), Surface Roughness, Material Removal Rate (MRR).