THE USE OF ARTIFICIAL NEURAL NETWORKS TO MODEL DISTORTION CAUSED BY WELDING

G. Bruce∗ and M. Lightfoot∗

Keywords

Distortion, prediction, design for production, welding, artificial neural networks

Abstract

Electric arc welding is the preferred joining process for many metal- using industries, from small sheet metal products to very large ships. Where thin-walled structures are built, the welding process causes the structure to distort, and this can lead to serious problems in fit up and assembly that require extensive rework. The mechanisms that lead to distortion have multiple causes, and thus modelling distortion in order to predict likely effects has in the past proved to be difficult. This paper outlines a novel approach using artificial neural networks, taking advantage of the ability to deal with multiple inputs. The results are promising, and further research is planned, alongside full-scale industrial trials of the software that has been developed.

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