Análise de dados de vida aplicada a um componente aeronáutico na otimização do seu intervalo de manutenção
By the end of the 50s, the aircraft fleet had grown exponentially and the maintenance costs had become significantly high, this fact made a more thorough study about maintenance techniques viable at that time. At the same time, the Federal Aviation Agency (FAA), responsible for regulating the preven...
| Autor principal: | Silva, Heric Ramos |
|---|---|
| Formato: | Trabalho de Conclusão de Curso (Especialização) |
| Idioma: | Português |
| Publicado em: |
Universidade Tecnológica Federal do Paraná
2020
|
| Assuntos: | |
| Acesso em linha: |
http://repositorio.utfpr.edu.br/jspui/handle/1/18681 |
| Tags: |
Adicionar Tag
Sem tags, seja o primeiro a adicionar uma tag!
|
| Resumo: |
By the end of the 50s, the aircraft fleet had grown exponentially and the maintenance costs had become significantly high, this fact made a more thorough study about maintenance techniques viable at that time. At the same time, the Federal Aviation Agency (FAA), responsible for regulating the preventive maintenance was frustrated at some studies showing that there was no control between reliability and preventive maintenance in some kinds of engines. This led to, in 1960, a task force between FAA and the airlines, aiming the investigation of the capabilities of preventive maintenance. This methodology is known to be successful regarding its application, causing great benefit and gain in preventive maintenance tasks, maintenance costs, availability of systems, spares etc. However, there are still some weakness to some points of this methodology which requires additional features. An example of it, that will be an object in this study, is the lack of probabilistic models in determining the maintenance strategies and maintenance intervals depending on the analyst’s own experience that can result in a bias and erroneous result. As a result of this study, it was possible to determine a maintenance interval for a specific component based on field data evidences, increasing in 25% the interval previously used. |
|---|