An Open Source Framework Approach to Support Condition Monitoring and Maintenance

Detalhes bibliográficos
Autor(a) principal: Campos, Jaime
Data de Publicação: 2020
Outros Autores: Sharma, Pankaj, Albano, Michele, Ferreira, Luís Lino, Larrañaga, Martin
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.22/18993
Resumo: This paper discusses the integration of emergent ICTs, such as the Internet of Things (IoT), the Arrowhead Framework, and the best practices from the area of condition monitoring and maintenance. These technologies are applied, for instance, for roller element bearing fault diagnostics and analysis by simulating faults. The authors first undertook the leading industry standards for condition-based maintenance (CBM), i.e., open system architecture–condition-based maintenance (OSA–CBM) and Machinery Information Management Open System Alliance (MIMOSA), which has been working towards standardizing the integration and interchangeability between systems. In addition, this paper highlights the predictive health monitoring methods that are needed for an effective CBM approach. The monitoring of industrial machines is discussed as well as the necessary details are provided regarding a demonstrator built on a metal sheet bending machine of the Greenbender family. Lastly, the authors discuss the benefits of the integration of the developed prototypes into a service-oriented platform, namely the Arrowhead Framework, which can be instrumental for the remotization of maintenance activities, such as the analysis of various equipment that are geographically distributed, to push forward the grand vision of the servitization of predictive health monitoring methods for large-scale interoperability.
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spelling An Open Source Framework Approach to Support Condition Monitoring and MaintenanceOSA–CBMRolling element bearing faultThe internet of thingsArrowhead frameworkThis paper discusses the integration of emergent ICTs, such as the Internet of Things (IoT), the Arrowhead Framework, and the best practices from the area of condition monitoring and maintenance. These technologies are applied, for instance, for roller element bearing fault diagnostics and analysis by simulating faults. The authors first undertook the leading industry standards for condition-based maintenance (CBM), i.e., open system architecture–condition-based maintenance (OSA–CBM) and Machinery Information Management Open System Alliance (MIMOSA), which has been working towards standardizing the integration and interchangeability between systems. In addition, this paper highlights the predictive health monitoring methods that are needed for an effective CBM approach. The monitoring of industrial machines is discussed as well as the necessary details are provided regarding a demonstrator built on a metal sheet bending machine of the Greenbender family. Lastly, the authors discuss the benefits of the integration of the developed prototypes into a service-oriented platform, namely the Arrowhead Framework, which can be instrumental for the remotization of maintenance activities, such as the analysis of various equipment that are geographically distributed, to push forward the grand vision of the servitization of predictive health monitoring methods for large-scale interoperability.The present work has been part of the MANTIS Cyber-Physical System based Proactive Collaborative Maintenance project, which has received funding from the Electronic Component Systems for European Leadership Joint Undertaking under grant agreement No 662189. The work was further developed in the context of the Productive 4.0 project, which has received funding from the Electronic Component Systems for European Leadership Joint Undertaking under grant agreement No 737459. The ECSEL Joint Undertaking receives support from the European Union’s Horizon 2020 research program.MDPIRepositório Científico do Instituto Politécnico do PortoCampos, JaimeSharma, PankajAlbano, MicheleFerreira, Luís LinoLarrañaga, Martin2021-12-06T14:30:01Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/18993eng10.3390/app10186360info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-03-13T13:12:26Zoai:recipp.ipp.pt:10400.22/18993Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:39:02.861398Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv An Open Source Framework Approach to Support Condition Monitoring and Maintenance
title An Open Source Framework Approach to Support Condition Monitoring and Maintenance
spellingShingle An Open Source Framework Approach to Support Condition Monitoring and Maintenance
Campos, Jaime
OSA–CBM
Rolling element bearing fault
The internet of things
Arrowhead framework
title_short An Open Source Framework Approach to Support Condition Monitoring and Maintenance
title_full An Open Source Framework Approach to Support Condition Monitoring and Maintenance
title_fullStr An Open Source Framework Approach to Support Condition Monitoring and Maintenance
title_full_unstemmed An Open Source Framework Approach to Support Condition Monitoring and Maintenance
title_sort An Open Source Framework Approach to Support Condition Monitoring and Maintenance
author Campos, Jaime
author_facet Campos, Jaime
Sharma, Pankaj
Albano, Michele
Ferreira, Luís Lino
Larrañaga, Martin
author_role author
author2 Sharma, Pankaj
Albano, Michele
Ferreira, Luís Lino
Larrañaga, Martin
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Repositório Científico do Instituto Politécnico do Porto
dc.contributor.author.fl_str_mv Campos, Jaime
Sharma, Pankaj
Albano, Michele
Ferreira, Luís Lino
Larrañaga, Martin
dc.subject.por.fl_str_mv OSA–CBM
Rolling element bearing fault
The internet of things
Arrowhead framework
topic OSA–CBM
Rolling element bearing fault
The internet of things
Arrowhead framework
description This paper discusses the integration of emergent ICTs, such as the Internet of Things (IoT), the Arrowhead Framework, and the best practices from the area of condition monitoring and maintenance. These technologies are applied, for instance, for roller element bearing fault diagnostics and analysis by simulating faults. The authors first undertook the leading industry standards for condition-based maintenance (CBM), i.e., open system architecture–condition-based maintenance (OSA–CBM) and Machinery Information Management Open System Alliance (MIMOSA), which has been working towards standardizing the integration and interchangeability between systems. In addition, this paper highlights the predictive health monitoring methods that are needed for an effective CBM approach. The monitoring of industrial machines is discussed as well as the necessary details are provided regarding a demonstrator built on a metal sheet bending machine of the Greenbender family. Lastly, the authors discuss the benefits of the integration of the developed prototypes into a service-oriented platform, namely the Arrowhead Framework, which can be instrumental for the remotization of maintenance activities, such as the analysis of various equipment that are geographically distributed, to push forward the grand vision of the servitization of predictive health monitoring methods for large-scale interoperability.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-01-01T00:00:00Z
2021-12-06T14:30:01Z
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.22/18993
url http://hdl.handle.net/10400.22/18993
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.3390/app10186360
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