Surface Roughness Prediction in End Milling of Machinable Glass Ceramic and Optimization By Response Surface Methodology

Abstract

This paper presents the prediction of a statistically analyzed model for the surfaceroughness of end-milled Machinable glass ceramic (MGC). Response Surface Methodology(RSM) is used to construct the models based on 3-factorial Box-Behnken Design (BBD). It is foundthat cutting speed is the most significant factor contributing to the surface roughness value followedby the depth of cut and feed rate. The surface roughness value decreases for higher cutting speedalong with lower feed and depth of cut. Additionally, the process optimization has also been donein terms of material removal rate (MRR) to the model’s response. Ideal combinations of machiningparameters are then suggested for common goal to achieve lower surface roughness value andhigher MRR.