Modeling and Analysis of Surface Roughness of AL7075-T6 in End Milling Process Using Response Surface Methodology

Abstract

The quality of the surface is significantly important for evaluating the productivity of machine tools and mechanical parts. Optimum cutting condition is an extremely important task as it determines the surface quality of the manufactured parts. In this paper, a statistical model has been developed to predict surface roughness in terms of tool geometry such as rake angle, nose radius of cutting tool and machining parameters such as cutting speed, cutting feed rate and axial depth of cut. Response surface methodology experimental design has been engaged in conducting experiments. The workpiece material is aluminum (AL7075-T6), and the tool used is high-speed steel end mill cutter with different geometry. The surface roughness of machined surface is measured by Mitutoyo Surf Test SJ201. The second-order mathematical model in terms of machining parameters was evolved for predicting surface roughness. The adequacy of the model was checked by employing ANOVA. The direct and interaction effect are graphically plotted which aids to study the significance of these parameters with surface roughness.