Veiga Suárez, Fernando
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Veiga Suárez
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Fernando
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Ingeniería
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Publication Open Access Symmetry and its application in metal additive manufacturing (MAM)(MDPI, 2022) Uralde Jiménez, Virginia; Veiga Suárez, Fernando; Aldalur, Eider; Suárez, Alfredo; Ballesteros Egüés, Tomás; Ingeniería; IngeniaritzaAdditive manufacturing (AM) is proving to be a promising new and economical technique for the manufacture of metal parts. This technique basically consists of depositing material in a more or less precise way until a solid is built. This stage of material deposition allows the acquisition of a part with a quasi-final geometry (considered a Near Net Shape process) with a very high raw material utilization rate. There is a wide variety of different manufacturing techniques for the production of components in metallic materials. Although significant research work has been carried out in recent years, resulting in the wide dissemination of results and presentation of reviews on the subject, this paper seeks to cover the applications of symmetry, and its techniques and principles, to the additive manufacturing of metals.Publication Open Access AI-driven predictive modeling of homogeneous bead geometry for WAAM processes(Springer, 2025-07-15) Fernández Zabalza, Aitor; Rodríguez Díaz, Álvaro; Veiga Suárez, Fernando; Suárez, Alfredo; Uralde Jiménez, Virginia; Ballesteros Egüés, Tomás; Alfaro López, José Ramón; Ingeniería; Ingeniaritza; Universidad Pública de Navarra / Nafarroako Unibertsitate PublikoaWith the increasing number of applications employing additive manufacturing solutions, these deposition processes must become more autonomous, which can be helped by the application of machine learning monitoring. This study presents a fully online, low-cost framework for real-time quality control in Invar wire-arc additive manufacturing (WAAM). Synchronized current and voltage signals are transformed into spatial heatmaps and temporal Markov transition images, which are processed by an optimized ResNet-18 to classify the quality of each layer on-the-fly. Validation using cross-validation on an internal Invar dataset yields an accuracy of up to 94% under clean conditions, with inference times below 20 ms per layer, enabling deployment during natural cooling between layers. These results demonstrate the feasibility of non-intrusive signal-based anomaly detection, enabling rapid identification of weld spalls and useful for scalable and automated WAAM monitoring in industrial environments.Publication Open Access Symmetry analysis in wire arc direct energy deposition for overlapping and oscillatory strategies in mild steel(MDPI, 2023) Uralde Jiménez, Virginia; Veiga Suárez, Fernando; Suárez, Alfredo; Aldalur, Eider; Ballesteros Egüés, Tomás; Ingeniería; IngeniaritzaThe field of additive manufacturing has experienced a surge in popularity over recent decades, particularly as a viable alternative to traditional metal part production. Directed energy deposition (DED) is one of the most promising additive technologies, characterized by its high deposition rate, with wire arc additive manufacturing (WAAM) being a prominent example. Despite its advantages, DED is known to produce parts with suboptimal surface quality and geometric accuracy, which has been a major obstacle to its widespread adoption. This is due, in part, to a lack of understanding of the complex geometries produced by the additive layer. To address this challenge, researchers have focused on characterizing the geometry of the additive layer, particularly the outer part of the bead. This paper specifically investigates the geometrical characteristics and symmetry of walls produced by comparing two different techniques: an oscillated strategy and overlapping beads.