Fuzzy Inference System for Prediction During Precision Turning Of Ti-6al-4v

AbstractThis research work focuses on precision turning of Ti6Al4V material to investigate the machinability of the material. Precision turning is a type of machining where, very low feed rate and depth of cut is being used to machine using a cutting insert with a lower nose radius. The cutting parameters considered for the experiments include the cutting speed, feed rate, depth of cut and nose radius. PVD coated carbide cutting inserts with different nose radius and constant rake and clearance angle are being considered for experimentation. The experimentation was designed based on Taguchi's L 27 orthogonal array. Three different levels of cutting parameters were being considered for the experimentation. The turning experiments were carried out on a conventional variable speed motor lathe under dry working conditions. Based upon the experimental values, Analysis of Variance (ANOVA) was conducted to understand the influence of various cutting parameters on cutting force, surface roughness and cutting tool temperatures during precision turning. There are a number of techniques available for predicting responses using input parameters and the present work uses Fuzzy Inference System (Mamdani Fuzzy logic) to predict the out put parameters