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Villanueva Roldán, Pedro

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Villanueva Roldán

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Pedro

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Ingeniería

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0000-0003-0865-3789

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2772

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  • PublicationUnknown
    Advances in robotic welding for metallic materials: application of inspection, modeling, monitoring and automation techniques
    (MDPI, 2023) Curiel Braco, David; Veiga Suárez, Fernando; Suárez, Alfredo; Villanueva Roldán, Pedro; Ingeniería; Ingeniaritza
    The robotic welding manufacturing of metal parts is a very important process, especially in heavy industries such as shipbuilding, oil and gas, automotive, and aerospace. There is a great variety of different techniques for manufacturing by robotic welding, and the welding operations are always in a constant process of evolution, as any advance can be significant to avoid defects during the welding process. Although a great deal of research work has been carried out in recent years, thanks to which results and reviews have been presented on this subject, the main aim of this publication is to define and review works that show the advances in the main inspection, modeling, monitoring, and automated operations during the welding process to avoid, or predictively identify, any possible defect in order to obtain an optimum degree of quality in the welding.
  • PublicationOpen Access
    Intelligent and adaptive system for welding process automation in T-shaped joints
    (MDPI, 2023) Aldalur, Eider; Suárez, Alfredo; Curiel Braco, David; Veiga Suárez, Fernando; Villanueva Roldán, Pedro; Ingeniería; Ingeniaritza
    The automation of welding processes requires the use of automated systems and equipment, in many cases industrial robotic systems, to carry out welding processes that previously required human intervention. Automation in the industry offers numerous advantages, such as increased efficiency and productivity, cost reduction, improved product quality, increased flexibility and safety, and greater adaptability of companies to market changes. The field of welding automation is currently undergoing a period of profound change due to a combination of technological, regulatory, and economic factors worldwide. Nowadays, the most relevant aspect of the welding industry is meeting customer requirements by satisfying their needs. To achieve this, the automation of the welding process through sensors and control algorithms ensures the quality of the parts and prevents errors, such as porosity, unfused areas, deformations, and excessive heat. This paper proposes an intelligent and adaptive system based on the measurement of welding joints using laser scanning and the subsequent analysis of the obtained point cloud to adapt welding trajectories. This study focuses on the optimization of T-joints under specific welding conditions and is intended as an initial implementation of the algorithm, thus establishing a basis to be worked on further for a broader welding application.