Volume 11 Issue 4 ( December 2024)

Aluminum metal matrix composites (MMCs) are widely recognized for their superior mechanical properties, making them essential in industries such as aerospace, automotive, electronics, and medical sectors. Despite extensive research in this area (R3,C1), this study presents a novel approach by optimizing the surface roughness of an Aluminum 6061 hybrid MMC reinforced with varying proportions of fly ash and silicon carbide (R2,C1). This research uniquely focuses on the interplay between critical turning parameters—depth of cut, feed, and cutting speed and their impact on surface roughness (R2,C1). To ensure the robustness of the findings, nine experimental0 trials were conducted using an L9 orthogonal array, chosen for its efficiency in exploring the parameter space. The test specimens were meticulously prepared using a controlled stir casting process, ensuring uniform dispersion of reinforcement particles within the aluminum matrix. The machining was performed on a high-speed CNC centre lathe, and the surface roughness was analysed using ANOVA (Analysis of Variance) to determine the significance of each parameter. Minitab software was employed to optimize the turning parameters, applying the Taguchi technique to achieve the desired surface finish. The optimal values of cutting speed, feed, and depth of cut were determined to be 3500 RPM, 0.15 mm/rev, and 0.3 mm, respectively. The findings reveal a significant improvement in surface roughness, which is quantified and benchmarked against industry standards. The study’s novelty (R2,C1) lies in its specific focus on hybrid MMCs (R3,C6)and the comprehensive analysis of turning parameters, providing valuable insights for industrial applications. However, the study acknowledges limitations (R3,C1), such as the focus on specific machining parameters and materials, suggesting avenues for future research (R3,C8), including the exploration of other composite materials and optimization techniques.

Keywords: Matrix Composite; Surface roughness; Taguchi method; MINITAB; ANOVA analysis ( R1,C4).