Universitat Politècnica de Catalunya. Departament d'Enginyeria Mecànica
Domènech Mestres, Carles
2026-01-27
This research assignment, conducted within the CASANDRA project, explores two key avenues for improving the manufacturing of large metal parts: the numerical modeling of welding processes and the use of Artificial Neural Networks for metal-sheet bending prediction. A bibliographic review provided insight into existing welding models and their limitations, particularly the need for experimentally calibrated parameters. The second part of the work focused on developing a simplified neural network based on theoretical bending equations to evaluate the potential of Machine Learning in forming operations. Although the results remained approximate, the study highlights the promise of AI-based methods for enhancing process accuracy and reducing operator dependency. Overall, the project emphasizes the value of combining simulation tools and data-driven approaches to support more efficient and modern industrial fabrication.
Incoming
Bachelor thesis
Anglès
Àrees temàtiques de la UPC::Enginyeria mecànica; Welding; Neural networks (Computer science); Strength of materials; Finite element method; Soldadura; Xarxes neuronals (Informàtica); Resistència de materials; Elements finits, Mètode dels
Universitat Politècnica de Catalunya
Open Access
Treballs acadèmics [82075]