Optimizing Surface Roughness and MRR in turning operation using Taguchi's design of experiments approach

The objective of this paper is to obtain an optimal setting of turning parameters (Speed, Feed, Depth of Cut and Nose Radius) which results in an optimal value of Surface Roughness and Material Removal Rate (MRR) while machining Al 6351-T6 alloy with Uncoated Carbide Inserts. Several statistical modeling techniques have been used to generate models including Genetic Algorithm, Response Surface Methodology. In our study, an attempt has been made to generate Regression model for Surface Roughness and MRR. Also we have made an attempt to optimize the process parameters using Taguchi technique to obtain optimum Surface Roughness and optimum MRR. S/N ratio and ANOVA analysis were also performed to obtain significant factors influencing Surface Roughness and MRR. © Research India Publications.