NEURAL NETWORKS APPROACH TO THE DETERMINATION OF THE MACHINING PARAMETERS

A neural networks based approach to determine the appropriate machinin g parameters such as speed, depth of cut and feed is proposed in this study. In this approach neural networks were used for building automat ic process planning systems. Training of neural networks was performed with back propagation method by using data sets sampled in a standard handbook. These networks consist of simple processing elements or nod es capable of processing information in response to external inputs. T his approach saves computing time and storage space. In addition, it p rovides easy extendability as new data become available. Currently, th e system provides three neural networks: for turning, for milling and for drilling operations. The performance of the trained neural network for drilling is evaluated to examine how well it predicts the machini ng parameters. Test results show that the neural network for the turni ng operation is able to predict the machining parameter values within an acceptable error rate.