Parameter selection by an artificial neural network for a laser bending process

Based on thermally induced plastic deformations produced by laser irradiation, metal sheet. laser bending can be a valid alternative to dies for rapid prototyping and manufacturing. Some numerical Models have been built in order to improve the understanding and prediction of mechanisms. Drawbacks entailed with those models. have been found. Finite element model simulation has Proved to be time and CPU (central processing, unit) memory consuming. The. analytical models. have been cumbersome and unsatisfactory. Nowadays, it is possible to build a neural network model for process modelling directly-from data collected during the experiments. In this paper a: feed-forward neural network with a back propagation learning function has been designed and its performances have been evaluated for metal sheet laser bending. This technique has proved to be effective and efficient, providing the process parameters that are necessary to achieve a desired bending angle..