Inteligencia Artificial para el soporte a la toma de decisiones en el ciclo de vida de los equipos industriales

• Miguel Ángel Mateo-Casalí ^[1] ; Juan Pablo Fiesco ^[1] ; Beatriz Andres ^[1] ; Raul Poler ^[1]
  1. [1] Universitat Politècnica de València
• Localización: Dirección y organización: Revista de dirección, organización y administración de empresas, ISSN 1132-175X, Nº 85, 2025, págs. 67-84
• Idioma: español
• DOI: 10.37610/85.691
• Títulos paralelos:
  • Artificial Intelligence for decision support in the lifecycle of industrial equipment
• Enlaces
  • Texto completo
• Resumen
  • español

    Este artículo realiza una revisión de la literatura sobre las aplicaciones de la IA en cada fase del ciclo de vida de los equipos industriales, incluyendo el diseño, la fabricación el uso y la reparación/reutilización/reciclado. Sobre la base del proyecto europeo AIDEAS, un conjunto de soluciones basadas en IA se conceptualiza. Estas soluciones se contextualizan en un piloto industrial que se dedica a la fabricación de equipos para la inspección y clasificación de alimentos. Las líneas futuras de investigación se dirigen hacia el desarrollo de las tecnologías de IA conceptualizadas, y su implementación en el piloto industrial objeto de estudio

  • English

    In the era of Industry 4.0, the application of Artificial Intelligence (AI) in the management and operation of industrial equipment has acquired a fundamental role. Maximising efficiency, minimising downtime and optimising the useful life of industrial equipment are, among others, the benefits that can be derived from implementing AI solutions throughout their lifecycle. AI has revolutionised the efficiency of the decision-making process. Supported by the European AIDEAS Project, this article aims to explore the integration of AI technologies in all stages of the life cycle of industrial equipment, from design to manufacturing, use and repair/reuse/recycling. To this end, a literature review is carried out to determine the application of AI in the different phases of a product's life cycle. Based on this, a set of solutions is conceptualised to be developed in the AIDEAS project. These solutions are contextualised in an industrial pilot for manufacturing food inspection and sorting equipment, illustrating the applicability of the AI solutions proposed in the AIDEAS project. Finally, future lines of research are directed towards the development of AI technologies in the AIDEAS project, and their implementation in the industrial pilot under study.

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