A Predictive Model for Surface Roughness in Turning Glass Fiber Reinforced Plastics by Carbide Tool (K-20) Using Soft Computing

Glass fiber reinforced plastics are finding its increased applications in various engineering fields such as aerospace, automobile, electronics and other industries. this paper discusses the use of fuzzy logic for modeling turning parameters in turning of glass fiber reinforced plastics by carbide tool (k-20). experiments were conducted based on the established taguchi.s design of experiments (doe) l25 orthogonal array on an all geared lathe. the cutting parameters considered were cutting speed, feed, depth of cut, and work piece (fiber orientation). fuzzy based model is developed for correlating the cutting parameters with surface roughness (ra). the results indicated that the model can be effectively used for predicting the surface roughness (ra) in turning of gfrp composites.