Reliability assessment using degradation models: bayesian and classical approaches

Detalhes bibliográficos
Autor(a) principal: Freitas,Marta Afonso
Data de Publicação: 2010
Outros Autores: Colosimo,Enrico Antonio, Santos,Thiago Rezende dos, Pires,Magda C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Pesquisa operacional (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382010000100010
Resumo: Traditionally, reliability assessment of devices has been based on (accelerated) life tests. However, for highly reliable products, little information about reliability is provided by life tests in which few or no failures are typically observed. Since most failures arise from a degradation mechanism at work for which there are characteristics that degrade over time, one alternative is monitor the device for a period of time and assess its reliability from the changes in performance (degradation) observed during that period. The goal of this article is to illustrate how degradation data can be modeled and analyzed by using "classical" and Bayesian approaches. Four methods of data analysis based on classical inference are presented. Next we show how Bayesian methods can also be used to provide a natural approach to analyzing degradation data. The approaches are applied to a real data set regarding train wheels degradation.
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spelling Reliability assessment using degradation models: bayesian and classical approachesBayesian approachclassical approachdegradation data analysisreliabilityTraditionally, reliability assessment of devices has been based on (accelerated) life tests. However, for highly reliable products, little information about reliability is provided by life tests in which few or no failures are typically observed. Since most failures arise from a degradation mechanism at work for which there are characteristics that degrade over time, one alternative is monitor the device for a period of time and assess its reliability from the changes in performance (degradation) observed during that period. The goal of this article is to illustrate how degradation data can be modeled and analyzed by using "classical" and Bayesian approaches. Four methods of data analysis based on classical inference are presented. Next we show how Bayesian methods can also be used to provide a natural approach to analyzing degradation data. The approaches are applied to a real data set regarding train wheels degradation.Sociedade Brasileira de Pesquisa Operacional2010-04-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382010000100010Pesquisa Operacional v.30 n.1 2010reponame:Pesquisa operacional (Online)instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)instacron:SOBRAPO10.1590/S0101-74382010000100010info:eu-repo/semantics/openAccessFreitas,Marta AfonsoColosimo,Enrico AntonioSantos,Thiago Rezende dosPires,Magda C.eng2010-05-27T00:00:00Zoai:scielo:S0101-74382010000100010Revistahttp://www.scielo.br/popehttps://old.scielo.br/oai/scielo-oai.php||sobrapo@sobrapo.org.br1678-51420101-7438opendoar:2010-05-27T00:00Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)false
dc.title.none.fl_str_mv Reliability assessment using degradation models: bayesian and classical approaches
title Reliability assessment using degradation models: bayesian and classical approaches
spellingShingle Reliability assessment using degradation models: bayesian and classical approaches
Freitas,Marta Afonso
Bayesian approach
classical approach
degradation data analysis
reliability
title_short Reliability assessment using degradation models: bayesian and classical approaches
title_full Reliability assessment using degradation models: bayesian and classical approaches
title_fullStr Reliability assessment using degradation models: bayesian and classical approaches
title_full_unstemmed Reliability assessment using degradation models: bayesian and classical approaches
title_sort Reliability assessment using degradation models: bayesian and classical approaches
author Freitas,Marta Afonso
author_facet Freitas,Marta Afonso
Colosimo,Enrico Antonio
Santos,Thiago Rezende dos
Pires,Magda C.
author_role author
author2 Colosimo,Enrico Antonio
Santos,Thiago Rezende dos
Pires,Magda C.
author2_role author
author
author
dc.contributor.author.fl_str_mv Freitas,Marta Afonso
Colosimo,Enrico Antonio
Santos,Thiago Rezende dos
Pires,Magda C.
dc.subject.por.fl_str_mv Bayesian approach
classical approach
degradation data analysis
reliability
topic Bayesian approach
classical approach
degradation data analysis
reliability
description Traditionally, reliability assessment of devices has been based on (accelerated) life tests. However, for highly reliable products, little information about reliability is provided by life tests in which few or no failures are typically observed. Since most failures arise from a degradation mechanism at work for which there are characteristics that degrade over time, one alternative is monitor the device for a period of time and assess its reliability from the changes in performance (degradation) observed during that period. The goal of this article is to illustrate how degradation data can be modeled and analyzed by using "classical" and Bayesian approaches. Four methods of data analysis based on classical inference are presented. Next we show how Bayesian methods can also be used to provide a natural approach to analyzing degradation data. The approaches are applied to a real data set regarding train wheels degradation.
publishDate 2010
dc.date.none.fl_str_mv 2010-04-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382010000100010
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0101-74382010000100010
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/S0101-74382010000100010
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
publisher.none.fl_str_mv Sociedade Brasileira de Pesquisa Operacional
dc.source.none.fl_str_mv Pesquisa Operacional v.30 n.1 2010
reponame:Pesquisa operacional (Online)
instname:Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron:SOBRAPO
instname_str Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
instacron_str SOBRAPO
institution SOBRAPO
reponame_str Pesquisa operacional (Online)
collection Pesquisa operacional (Online)
repository.name.fl_str_mv Pesquisa operacional (Online) - Sociedade Brasileira de Pesquisa Operacional (SOBRAPO)
repository.mail.fl_str_mv ||sobrapo@sobrapo.org.br
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