Abstract
The present work aims to design an artificial neural network (ANN) for controlling the geometry of the fusion zone in different welding conditions. AA5754 aluminium plates with 6 mm thickness were welded in butt configuration by using an Yb-doped fiber laser in continuous wave regime. Laser power, travel speed, beam diameter and shielding gas were considered as process-related factors, while the weld geometry was evaluated in terms of penetration depth and bead width. The accuracy of the model was endorsed by using untrained test data. Results showed a good agreement between the ANN output and the experimental values.
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