Development of Surface Roughness Prediction Model for Titanium Alloys in Milling

Surface roughness plays on important role in manufacturing and the product quality depends on the surface roughness. The present work focuses on developing a multiple regression model with intercepts for the prediction of surface roughness of Titanium alloys machined on CNC milling machine. The working parameters, viz. speed, feed and depth of cut and surface roughness as response are considered in this model. The experiments were conducted based on factorial design using Design of Experiments (DOE). The prediction models are developed using Multiple regression techniques with and with out interaction terms of both Linear and Non Linear. The values of surface roughness predicted by this model are then verified with additional experimental results. Experimental results and regression analysis demonstrate that the model developed in this work predicts the surface roughness values with good accuracy.