From CAD to computer aided welding

Within the context of integrated design, we propose a new approach for off-line programming of welding robots by interfacing a CAD modeller (geometric database) and an artificial intelligence system (welding database). The CAD system associated with our development, used to design the parts to be assembled, allows us to generate welding paths automatically and to extract the assembly features required to determine welding parameters. With these features, we propose a new approach to generate welding parameters automatically in the GMAW process with neural networks. We have chosen to use backpropagation neural networks as this approach integrates database and modelling aspects. Moreover, a neural net based system can easily be improved, it can enlarge its field of application using new experimental welding data. In this paper we present the system we have developed for the generation of paths and then an approach using neural networks to determine welding parameters. We show how CAD features can be used to determine the welding process, the welding wire and then to compute welding parameters.