Objective: The present work is aimed to find an optimum combination of cutting parameters to achieve low surface roughness in end milling of magnesium AM60 with TiN coated carbide tool under dry conditions. Methods: Design of Experiments (DOE) with Response Surface Methodology (RSM) using Box-Behnken design and the regression equations are used to find the optimal combinations of cutting parameters to achieve low surface roughness. The developed RSM model was experienced through Analysis of Variance (ANOVA). An ANOVA analysis was performed to indicate the control of three machining parameters on the surface roughness. Findings: The cutting parameters assessed were spindle speed, depth of cut and feed rate have the greatest effect on the success of the milling operation. Confirmation experiments with the optimum combinations of cutting parameters were carried out in order to explain the efficiency of the response surface design concepts. From ANOVA results, the feed rate was found to be most significant factor affects surface roughness of milled surface. Feed rate, depth of cut and spindle speed affects the surface roughness by 76.18%, 2.94% and 1.99% respectively. It can be fulfilled that RSM method is effective and efficient method to optimize milling parameters for low surface roughness. Applications: Magnesium (Mg) is now emerging as a popular metal for replacing Aluminum (Al) and finding applications in automobile and aerospace industries where fine finishing of the machined component is ultimate requirements to achieve a product quality.
Keywords
End Milling, Magnesium, Response Surface Methodology, Surface Roughness
User
Information