Soft Computing Applications in Drilling of GFRP Composites: A Review

Abstract

Glass fiber reinforced plastics (GFRP) are finding increased applications in various engineering fields such as aerospace, automotive, electronics and other industries. Among the various machining processes, drilling is the important process, mainly used in joining of composite structures. As a consequence, the number of authors have discussed on the aspects concerning the machiniability of GFRP composites. In this study, a review has been done on the machinability of drilling of GFRP composites through the various aspects such as tool materials and geometry, machining parameters and their influence on thrust force, torque, surface roughness, delamination factor and hole damage. Additionally, the modeling of the machining parameters on drilling of GFRP composites using response surface methodology (RSM), artificial neural network (ANN), fuzzy logic, NSGA-II etc., have been discussed. The results indicated that the thrust force, torque and surface roughness need to be controlled simultaneously for delamination free drilling. Further, there is a need to create a multi-response optimization in drilling of GFRP composites using different optimization techniques for obtaining optimum results of thrust force, torque, surface roughness and delamination free drilling.