Development of surface roughness prediction model using response surface methodology in high speed end milling of AISI H13 tool steel

This paper presents a study on the development of an effective method to predict surface roughness for high speed end milling of AISI H13 tool steel using PCBN inserts. The response surface methodology (RSM) has been utilized for the postulation of a second order quadratic model in terms of cutting speed, axial depth of cut and feed. Sufficient numbers of experiments were run based on the Box-Wilson central composite design (CCD) concept of RSM in order to generate roughness data. The ANOVA technique has been used to verify the adequacy of the model at 95% confidence interval. From the model it was found that feed plays the most dominating role on surface finish followed by the cutting speed. However, axial depth of cut does not have significant effect on roughness value. The roughness tends to decrease with decreasing feed and increasing cutting speed.