MATHEMATICAL MODELLING FOR SURFACE ROUGHNESS OF STIR CAST Al-RHA REINFORCED COMPOSITE USING REGRESSION ANALYSIS

Abstract

Surface Roughness and Material removal rate are the important characteristics affecting quality of a material. Surface roughness is a product quality index which is employed to check the quality of a product . As surface finish increases, mechanical properties of a product also become strengthened. Therefore , surface roughness factor decides the quality of a product. Surface Roughness affects the product life as well as other factors like friction, heat transmission, temperature etc. By analyzing the parameter called surface roughness, we are tending towards the optimal level of machining parameters which leads to low production cost by reducing production time. In the study, focus is being based on the fabrication of aluminium 6061 metal matrix composite reinforced with RHA(rice husk ash ). 8wt% RHA is incorporated to the matrix by using stir casting technique. This study investigates the effect of input variables like cutting speed , feed rate , depth of cut on response variable or output variable as surface roughness. Taguchi method has been used to optimize the machining parameters, which is a influential parameter for analyzing optimal level of parameter. The specimen was machined under different parameters and was being measured for surface roughness under varying machining parameters using Taylor Hubson's Surtronic 3+. The optimum parameters are cutting speed (V) ,feed (f), depth of cut (d) which produces minimum surface roughness of material. From the results, it is revealed that high cutting speed and low feed rate causes better surface finish.