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Previsão de falhas em infraestruturas e equipamentos com recurso a técnicas de data mining

Authors: Charrua, José Rafael Lopes Silva;

Previsão de falhas em infraestruturas e equipamentos com recurso a técnicas de data mining

Abstract

Um Aeroporto internacional reúne um conjunto complexo de instalações, equipamentos e serviços, de difícil gestão e que funciona permanentemente, sendo premente a sua disponibilidade em condições de operação e utilização. A previsão de falhas e avarias reveste-se de uma grande importância para o aumento da disponibilidade da infraestrutura, bem como para uma gestão eficiente dos recursos humanos alocados à manutenção. Com a previsão de indisponibilidade de equipamentos ou infraestruturas poder-se-ão ainda tomar decisões atempadas e eficazes para a realização de manutenção preventiva, bem como para a gestão dos fluxos de passageiros ou até mesmo de aeronaves. Pretende este trabalho demonstrar a fiabilidade de um modelo de previsão de avarias numa infraestrutura aeroportuária através de técnicas de Data Miningaplicadas à base de dados do Sistema de Gestão de Manutenção do Aeroporto de Lisboa. Para além das questões de ordem técnica e operacional, existe outro problema interessante de responder, que é o de demonstrar aos gestores a importância das previsões/modelos criados para a organização em que se insere o estudo de caso. Se os modelos tiverem qualidade suficientee se a organização se decidir pela sua incorporação, poder-se-á posteriormente medir o impacto da sua aplicação.

An international airport encloses a complex set of facilities, equipments and services which are difficult to manage and have to operate permanently. The accessibility of operating and usage conditions is of utmost importance. Forecasting failures and malfunctions, to increase the infrastructure’s performance, as well as managing the human resources allocated to maintenance efficiently is a matter of major significance. By forecasting the equipment or infrastructure unavailability it is also possible to make timely and efficient decisions to perform a preventive maintenance, and also to manage the passengers and even aircrafts’ flow. This work demonstrates the dependability of a malfunction forecast model for an airport infrastructure, through Data Miningtechniques, applied to the Lisbon Airport Maintenance Management System data base. Besides the issues of technical and operational nature, there is another interesting problem which is to demonstrate the managers the importanceof forecasts/models, created for the company used in the case study. If the models have sufficient quality and if the company decides on its incorporation, then it will be possible to measure the impact of its application.

Country
Portugal
Keywords

Inteligência empresarial, Airports, Aeroportos, Aeroporto -- Airport, Forecast, Maintenance management, Previsão, Domínio/Área Científica::Engenharia e Tecnologia::Outras Engenharias e Tecnologias, Data mining, Gestão de manutenção, Data mining --, Business intelligence

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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