Surface Roughness Parameters Evaluation in Machining GFRP Composites by PCD Tool using Digital Image Processing

Abstract

Glass fiber reinforced polymer (GFRP) composites find diverse applications in many fields. Their usage in modern automated manufacturing sector demand high quality components and high finish surfaces. As such the present paper makes a study of the surface roughness of the machined surfaces of GFRP composites at different cutting conditions. The GFRP pipes are turned in lathe using Poly-Crystalline Diamond (PCD) tool. During machining, the machined surface images are captured using a Charge Coupled Device (CCD) camera. For all the images average grey scale value (Ga) are calculated. The average grey scale values and surface roughness (Ra) values are correlated and a relation is obtained between them. Also a second order quadratic model is developed for predicting surface roughness in machining of GFRP composites. The results indicate that the developed model can be used to predict the surface roughness of machined GFRP composites. The grey scale values obtained are in good correlation with the surface roughness values measured. The effect of cutting speed, feed, depth of cut and fiber orientation angle on surface roughness is studied and found that feed affects surface roughness, followed by cutting speed and fiber orientation angle. Depth of cut is found to have no effect on surface roughness of machined GFRP composites.