Analysis of the influence of deposition parameters on wire arc additive manufacturing of aluminium 6061 using ANN

Abstract As a transformative technology, additive manufacturing has become essential for fabricating complex and customized components. Leveraging Metal Inert Gas welding, as an emerging layer-by-layer fabrication method, Wire Arc Additive Manufacturing (WAAM) Method de- livers significant advantages in material utilization, build rate, and cost-efficient method for fabricating full-scale components. This technique was evaluated on Aluminium 6061 mate- rial, renowned for its extensive industrial applications in constructing large structures. Given the importance of bead deposition Single-bead depositions were carried out by adopting the WAAM process for subsequent analysis. An in-depth statistical evaluation of the input pa- rameters affecting bead geometry was performed, resulting in the formulation of regression models for accurate prediction. An Artificial Neural Network(ANN) based predictive system was utilized to estimate geometric features, with the results verified through experimental observations. A multi-objective optimization approach was employed for identifying the most suitable configuration of process specifications required to obtain the preferred bead geometry. Multi-layer walls produced through a single-pass process of Aluminium 6061 were successfully produced through the WAAM process, utilizing the optimized specifica- tions. Validation revealed a refined microstructure of excellent quality, free from porosity and cracks.