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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Predi??o em modelos de tempo de falha acelerado com efeito aleat?rio para avalia??o de riscos de falha em po?os petrol?feros

Carvalho, Jo?o Batista 28 May 2010 (has links)
Made available in DSpace on 2015-03-03T15:28:31Z (GMT). No. of bitstreams: 1 JoaoBC_DISSERT_partes_autorizadas.pdf: 252147 bytes, checksum: e830f27faffa86c9087da28e43e699fd (MD5) Previous issue date: 2010-05-28 / Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior / We considered prediction techniques based on models of accelerated failure time with random e ects for correlated survival data. Besides the bayesian approach through empirical Bayes estimator, we also discussed about the use of a classical predictor, the Empirical Best Linear Unbiased Predictor (EBLUP). In order to illustrate the use of these predictors, we considered applications on a real data set coming from the oil industry. More speci - cally, the data set involves the mean time between failure of petroleum-well equipments of the Bacia Potiguar. The goal of this study is to predict the risk/probability of failure in order to help a preventive maintenance program. The results show that both methods are suitable to predict future failures, providing good decisions in relation to employment and economy of resources for preventive maintenance. / Consideramos t?cnicas de predi??o baseadas em modelos de tempo de falha acelerado com efeito aleat?rio para dados de sobreviv?ncia correlacionados. Al?m do enfoque bayesiano atrav?s do Estimador de Bayes Emp?rico, tamb?m discutimos sobre o uso de um m?todo cl?ssico, o Melhor Preditor Linear N?o Viciado Emp?rico (EBLUP), nessa classe de modelos. Para ilustrar a utilidade desses m?todos, fazemos aplica??es a um conjunto de dados reais envolvendo tempos entre falhas de equipamentos de po?os de petr?leo da Bacia Potiguar. Neste contexto, o objetivo ? predizer os riscos/probabilidades de falha com a finalidade de subsidiar programas de manuten??o preventiva. Os resultados obtidos mostram que ambos os m?todos s?o adequados para prever falhas futuras, proporcionando boas decis?es em rela??o ao emprego e economia de recursos para manuten??o preventiva

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