Parametric Optimization of Drilling Machining Process of M.S.Material by Using Factorial Regression Method

Abstract

This thesis presents a method for finding the most influential factor amongst the Feed Rate, Speed of the Spindle and Depth of Cut to get the highest removal rate of material and superior surface finish using multi-factor Anova analysis. In any manufacturing industry, it is important that the input parameters are optimized to get the desired output in say minimum time, minimum cost and with high quality. In a metal turning or milling shop the most important input parameters are usually Feed Rate, Speed of the Spindle and Depth of Cut. The common desired outcomes are high Removal Rate of Material (MRR) and good Finish of Surface. Hence to optimize the input parameters, number of experiments were conducted at different spindle speeds, feed rates & depth of cuts and outputs in terms of MRR and surface finish were measured. These outputs were then analyzed using multi factor factorial analysis using Minitab Software. The observation were that, the Depth of cut had significant authority on the Material Removal Rate, however feed rates and spindle speed had comparatively less effect on it. As far as the Surface Roughness was concerned, both the Speed of Spindle and Depth of Cut had significant share of significance on the Surface Roughness values.