6533b7d7fe1ef96bd126829b

RESEARCH PRODUCT

Neural Network Techniques for Metal Forming Design

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Neural networks are computing structures able to predict the behaviour of a system on the basis of the knowledge of facts; main characteristic of a network is the capability to find a rule in a very complex environment. In the paper a neural network, based on the results of FEM simulations, is utilized to predict the occurrence of defects in a forward extrusion metal forming process. In particular a three layers neural network, relating the operative parameters with the failure or the success of the working process, has been used and the back-propagation algorithm has been employed to train the network. Few experimental data were enough to train the neural network allowing to achieve better results than the ones obtained by means of the common discriminant analysis.