Statistical Process Control based on Multivariate Image Analysis: A new proposal for monitoring and defect detection

The monitoring, fault detection and visualization of defects are a strategic issue for product quality. This paper presents a novel methodology based on the integration of textural Multivariate image analysis (MIA) and multivariate statistical process control (MSPC) for process monitoring. The propo...

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Autores: Prats-Montalbán, José Manuel|||0000-0001-6294-4486, Ferrer, Alberto|||0000-0001-7244-5947
Formato: artículo
Fecha de publicación:2014
País:España
Recursos:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/50302
Acesso em linha:https://riunet.upv.es/handle/10251/50302
Access Level:acceso abierto
Palavra-chave:Multivariate Image Analysis (MIA)
ARL
Control charts
RSS image
T2 image
Wavelets
ESTADISTICA E INVESTIGACION OPERATIVA
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repository_id_str
spelling Statistical Process Control based on Multivariate Image Analysis: A new proposal for monitoring and defect detectionPrats-Montalbán, José Manuel|||0000-0001-6294-4486Ferrer, Alberto|||0000-0001-7244-5947Multivariate Image Analysis (MIA)ARLControl chartsRSS imageT2 imageWaveletsESTADISTICA E INVESTIGACION OPERATIVAThe monitoring, fault detection and visualization of defects are a strategic issue for product quality. This paper presents a novel methodology based on the integration of textural Multivariate image analysis (MIA) and multivariate statistical process control (MSPC) for process monitoring. The proposed approach combines MIA and p-control charts, as well as T2 and RSS images for defect location and visualization. Simulated images of steel plates are used to illustrate the monitoring performance of it. Both approaches are also applied on real clover images.The authors want to thank Ole Mathis Kruse and Prof. Cecilia Futsaether, from the Norwegian University of Life Sciences (Dept. of Mathematic Sciences and Technology), for providing the real image data set. This research work was partially supported by the Spanish Ministry of Economy and Competitiveness under the project DPI 2011-28112-C04-02.ElsevierDepartamento de Estadística e Investigación Operativa Aplicadas y CalidadEscuela Técnica Superior de Ingeniería IndustrialGrupo de Ingeniería Estadística Multivariante GIEMMinisterio de Ciencia e InnovaciónRepositorio Institucional de la Universitat Politècnica de València Riunet20142014-12-04journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://riunet.upv.es/handle/10251/50302reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengMinisterio de Ciencia e Innovación http://dx.doi.org/10.13039/501100004837 DPI2011-28112-C04-02 MONITORIZACION, INFERENCIA, OPTIMIZACION Y CONTROL MULTI-ESCALA: DE CELULAS A BIORREACTORES. (MULTISCALES)open accesshttp://purl.org/coar/access_right/c_abf2Reserva de todos los derechoshttp://rightsstatements.org/vocab/InC/1.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/503022026-06-13T07:49:27Z
dc.title.none.fl_str_mv Statistical Process Control based on Multivariate Image Analysis: A new proposal for monitoring and defect detection
title Statistical Process Control based on Multivariate Image Analysis: A new proposal for monitoring and defect detection
spellingShingle Statistical Process Control based on Multivariate Image Analysis: A new proposal for monitoring and defect detection
Prats-Montalbán, José Manuel|||0000-0001-6294-4486
Multivariate Image Analysis (MIA)
ARL
Control charts
RSS image
T2 image
Wavelets
ESTADISTICA E INVESTIGACION OPERATIVA
title_short Statistical Process Control based on Multivariate Image Analysis: A new proposal for monitoring and defect detection
title_full Statistical Process Control based on Multivariate Image Analysis: A new proposal for monitoring and defect detection
title_fullStr Statistical Process Control based on Multivariate Image Analysis: A new proposal for monitoring and defect detection
title_full_unstemmed Statistical Process Control based on Multivariate Image Analysis: A new proposal for monitoring and defect detection
title_sort Statistical Process Control based on Multivariate Image Analysis: A new proposal for monitoring and defect detection
dc.creator.none.fl_str_mv Prats-Montalbán, José Manuel|||0000-0001-6294-4486
Ferrer, Alberto|||0000-0001-7244-5947
author Prats-Montalbán, José Manuel|||0000-0001-6294-4486
author_facet Prats-Montalbán, José Manuel|||0000-0001-6294-4486
Ferrer, Alberto|||0000-0001-7244-5947
author_role author
author2 Ferrer, Alberto|||0000-0001-7244-5947
author2_role author
dc.contributor.none.fl_str_mv Departamento de Estadística e Investigación Operativa Aplicadas y Calidad
Escuela Técnica Superior de Ingeniería Industrial
Grupo de Ingeniería Estadística Multivariante GIEM
Ministerio de Ciencia e Innovación
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Multivariate Image Analysis (MIA)
ARL
Control charts
RSS image
T2 image
Wavelets
ESTADISTICA E INVESTIGACION OPERATIVA
topic Multivariate Image Analysis (MIA)
ARL
Control charts
RSS image
T2 image
Wavelets
ESTADISTICA E INVESTIGACION OPERATIVA
description The monitoring, fault detection and visualization of defects are a strategic issue for product quality. This paper presents a novel methodology based on the integration of textural Multivariate image analysis (MIA) and multivariate statistical process control (MSPC) for process monitoring. The proposed approach combines MIA and p-control charts, as well as T2 and RSS images for defect location and visualization. Simulated images of steel plates are used to illustrate the monitoring performance of it. Both approaches are also applied on real clover images.
publishDate 2014
dc.date.none.fl_str_mv 2014
2014-12-04
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/50302
url https://riunet.upv.es/handle/10251/50302
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Ministerio de Ciencia e Innovación http://dx.doi.org/10.13039/501100004837 DPI2011-28112-C04-02 MONITORIZACION, INFERENCIA, OPTIMIZACION Y CONTROL MULTI-ESCALA: DE CELULAS A BIORREACTORES. (MULTISCALES)
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reserva de todos los derechos
http://rightsstatements.org/vocab/InC/1.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869413354795171841
score 15,301603

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