Optimization of Surface Roughness in End Milling Using Potential Support Vector Machine

This paper is concerned with the optimization of the surface roughness when milling aluminium alloys (AA6061-T6) with carbide coated inserts. Optimization of milling is very useful to reduce cost and time for machining mould. Potential support vector machine (PSVM) is used to develop surface roughness predicted model. Design of experiments method and response surface methodology techniques are implemented. The validity test of the fit and adequacy of the proposed models has been carried out through analysis of variance. The experiments results are compared with predictive model developed by PSVM. The optimum machining conditions in favor of surface roughness are estimated and verified with proposed optimized results. It is observed that the developed model is within the limits of the agreeable error (about 2–9 %) when compared to experimental results.