Drilling of Polycarbonate/Glass Fibre Polymer Composite-Modelling Using Artificial Neural Networks

The aim of this paper is to structure ANN models which are capable of predicting the variations in the cutting forces, on drilling polycarbonate/glass fibre polymer composite material. The experimental observations were made at some selected cutting speed and feed combinations by drilling unified, 10%, and 20% glass filled polycarbonate, using HSS and carbide tipped drill bits of 6mm diameter. Appreciable amount of reduction in the cutting forces was found, when drilled with WC tipped drill bits. So developed, back propagation paradigm based ANN models with delta learning rule predicts, abovementioned variations with exceptional accuracy.