Application of grey fuzzy logic for the optimization of drilling parameters for CFRP composites with multiple performance characteristics

Carbon Fibre Reinforced Plastic (CFRP) composite materials have potential applications in various domains. In machining, drilling is essentially required to join different structures. But CFRP drilling poses many problems that decrease the quality of holes. In this paper, Taguchi’s L27 orthogonal array is used to perform drilling of CFRP composite plates. To improve the quality of the holes drilled, the optimal combination of drilling parameters is chosen using grey relational analysis. Grey fuzzy optimization of drilling parameters is based on five different output performance characteristics, namely, thrust force, torque, entry delamination, exit delamination and eccentricity of the holes. Analysis of variance (ANOVA) is used to find the percentage contribution of the drilling parameters and found that feed rate is the most influential factor in drilling of CFRP composites.

► High speed steel (HSS) drills with three different point angles are used for drilling of CFRP composites.
► Thrust force, torque, entry-delamination, exit-delamination and eccentricity indicate quality of holes.
► A multiple performance optimization, grey fuzzy analysis is used for finding optimal drilling parameters for quality holes.
► It is seen that high spindle speed, low point angle and low feed rate produces quality holes, with minimum defects.