Experimental investigation of surface roughness and delamination using artificial intelligence

Glass Fiber Reinforced Plastics (GFRP) is considered to be an economic substitute to numerous heavy exotic materials and used in a variety of applications from aircraft to machine tools due to their light weight, high modulus, specific strength and high fracture toughness. Machining of FRP composites is a problematic task because of its unique natureand they are made very close to the final shape and any successive milling is inadequate due to surface roughness, delamination, deburring and trimming and to achieve contour shape accuracy. Delamination occurs during milling of GFRP and it’s the big headache for the industries. In this paper, the optimized parameters which results in minimum delamination and a smooth surface during milling of GFRP are analyzed. The main purpose of this paper is to estimate the surface roughness and delamination of the Glass Fiber Reinforced Plastics (GFRP) using Python.