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 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.Publication Open Access Advanced welding automation: Intelligent systems for multipass welding in Butt Double V-Groove and Tee Double Bevel configurations(Elsevier, 2024-12-01) Curiel Braco, David; Suárez, Alfredo; Veiga Suárez, Fernando; Aldalur, Eider; Villanueva Roldán, Pedro; Ingeniería; IngeniaritzaThe paper addresses the imperative shift towards automation in welding processes, leveraging advanced technologies such as industrial robotic systems. Focusing on the reconstruction and classification of weld joints, it introduces a methodology for automatic trajectory determination. Utilizing a laser profilometer mounted on the robot, weld joints are reconstructed in three di- mensions, and spurious data is filtered out through signal processing. A classification algorithm, integrating signal processing and artificial intelligence, accurately categorizes joint profiles, in- cluding V-joints and single bevel T-joints. The proposed intelligent and adaptive system enhances welding automation by analyzing point cloud data from laser scanning to optimize welding tra- jectories. This study establishes a foundational framework for further refinement and broader application in welding automation. Key Points - Introduction of a methodology for automated trajectory determination in welding processes. - Utilization of laser scanning and signal processing for reconstruction and classification of weld joints. - Implementation of an intelligent and adaptive system to optimize welding trajectoriesPublication 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.