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| 5.52 MB | Adobe PDF |
Advisor(s)
Abstract(s)
Esta dissertação apresenta um estudo sobre a função manutenção, considerada fundamental para as organizações, pois é essencial para garantir a continuidade dos processos de produção, a prestação de serviços com qualidade e para assegurar que os equipamentos e instalações funcionem de forma eficiente e segura. Este trabalho tem como objetivo principal, desenvolver uma solução com recurso a técnicas de inteligência artificial para otimizar o planeamento da manutenção de equipamentos médicos, assim como suportar a gestão da manutenção nas suas tomadas de decisão. Foram recolhidos dados de funcionamento de equipamentos médicos, aos quais foram aplicados diferentes algoritmos de aprendizagem de machine learning (aprendizagem automática) de modo a identificar o melhor modelo em termos de precisão e exatidão que se aplica à resolução do objetivo proposto. Espera-se demonstrar que a solução desenvolvida contribuirá não só para a otimização do planeamento, bem como para prolongar o ciclo vida útil dos equipamentos, evitando falhas, diminuindo os tempos de inatividade e reduzindo os custos de manutenção.
This thesis offers a study about maintenance, considered essential for organizations, as it’s essential to ensure the stability of production processes, the delivery of quality services and to ensure that equipment and installations operate efficiently and safely. The main objective of this work is to develop a solution using artificial intelligence techniques to optimize the maintenance planning of medical equipment, as well as to support maintenance management in their decisions. Medical equipment operating data was collected, different machine learning algorithms was applied to identify the best model in terms of precision and accuracy that be appropriate to the resolution of the proposed objective. It’s expected to demonstrate that the developed solution will contribute not only to the optimization of planning, but also to extend the useful life cycle of the equipment, avoiding failures, reducing downtime, and reducing maintenance costs.
This thesis offers a study about maintenance, considered essential for organizations, as it’s essential to ensure the stability of production processes, the delivery of quality services and to ensure that equipment and installations operate efficiently and safely. The main objective of this work is to develop a solution using artificial intelligence techniques to optimize the maintenance planning of medical equipment, as well as to support maintenance management in their decisions. Medical equipment operating data was collected, different machine learning algorithms was applied to identify the best model in terms of precision and accuracy that be appropriate to the resolution of the proposed objective. It’s expected to demonstrate that the developed solution will contribute not only to the optimization of planning, but also to extend the useful life cycle of the equipment, avoiding failures, reducing downtime, and reducing maintenance costs.
Description
Keywords
Planeamento Manutenção Preditiva Inteligência Artificial Machine Learning Algoritmos Planning Predictive Maintenance Artificial Intelligence Machine Learning Algorithms