Publicação
Industrial IoT devices and cyber-physical production systems: review and use case
| Resumo: | The present paper describes the state of the art related to IIoT Devices and Cyber-Physical systems and presents a use case related to predictive maintenance. Industry 4.0 is the boost for smart manufacturing and demands flexibility and adaptability of all devices/machines in the shop floor. The machines must become smart and interact with other machines inside and outside the industries/factories. The predictive maintenance is a key topic in this industrial revolution. The reason is based on the idea that smart machines must be capable to automatically identify and predict possible faults and actuate before they occur. Vibrations can be problematic in electrical motors. For this reason, we address an experimental study associated with an automatic classification procedure, that runs in the smart devices to detect anomalies. The results corroborate the applicability and usefulness of this machine learning algorithm to predict vibration faults. |
|---|---|
| Autores principais: | Rubio, Eva Masero |
| Outros Autores: | Dionísio, Rogério Pais; Torres, Pedro |
| Assunto: | Cyber-physical systems Industrial IoT Smart factories Machine learning Predictive maintenance |
| Ano: | 2019 |
| País: | Portugal |
| Tipo de documento: | capítulo de livro |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Instituto Politécnico de Castelo Branco |
| Idioma: | inglês |
| Origem: | Repositório Científico do Instituto Politécnico de Castelo Branco |
| _version_ | 1864888265354510336 |
|---|---|
| author | Rubio, Eva Masero |
| author2 | Dionísio, Rogério Pais Torres, Pedro |
| author2_role | author author |
| author_facet | Rubio, Eva Masero Dionísio, Rogério Pais Torres, Pedro |
| author_role | author |
| contributor_name_str_mv | Repositório Científico do Instituto Politécnico de Castelo Branco |
| country_str | PT |
| creators_json_str | [{\"Person.name\":\"Rubio, Eva Masero\"},{\"Person.name\":\"Dionísio, Rogério Pais\",\"Person.identifier.orcid\":\"0000-0002-6810-2447\"},{\"Person.name\":\"Torres, Pedro\",\"Person.identifier.orcid\":\"0000-0003-4835-5022\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Repositório Científico do Instituto Politécnico de Castelo Branco |
| datacite.creators.creator.creatorName.fl_str_mv | Rubio, Eva Masero Dionísio, Rogério Pais Torres, Pedro |
| datacite.date.Accepted.fl_str_mv | 2019-01-01T00:00:00Z |
| datacite.date.available.fl_str_mv | 2020-12-31T01:30:21Z |
| datacite.date.embargoed.fl_str_mv | 2020-12-31T01:30:21Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Cyber-physical systems Industrial IoT Smart factories Machine learning Predictive maintenance |
| datacite.titles.title.fl_str_mv | Industrial IoT devices and cyber-physical production systems: review and use case |
| dc.contributor.none.fl_str_mv | Repositório Científico do Instituto Politécnico de Castelo Branco |
| dc.creator.none.fl_str_mv | Rubio, Eva Masero Dionísio, Rogério Pais Torres, Pedro |
| dc.date.Accepted.fl_str_mv | 2019-01-01T00:00:00Z |
| dc.date.available.fl_str_mv | 2020-12-31T01:30:21Z |
| dc.date.embargoed.fl_str_mv | 2020-12-31T01:30:21Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10400.11/6097 |
| dc.language.none.fl_str_mv | eng |
| dc.publisher.none.fl_str_mv | Springer |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Cyber-physical systems Industrial IoT Smart factories Machine learning Predictive maintenance |
| dc.title.fl_str_mv | Industrial IoT devices and cyber-physical production systems: review and use case |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_3248 |
| description | The present paper describes the state of the art related to IIoT Devices and Cyber-Physical systems and presents a use case related to predictive maintenance. Industry 4.0 is the boost for smart manufacturing and demands flexibility and adaptability of all devices/machines in the shop floor. The machines must become smart and interact with other machines inside and outside the industries/factories. The predictive maintenance is a key topic in this industrial revolution. The reason is based on the idea that smart machines must be capable to automatically identify and predict possible faults and actuate before they occur. Vibrations can be problematic in electrical motors. For this reason, we address an experimental study associated with an automatic classification procedure, that runs in the smart devices to detect anomalies. The results corroborate the applicability and usefulness of this machine learning algorithm to predict vibration faults. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | bookPart |
| fulltext.url.fl_str_mv | https://repositorio.ipcb.pt/bitstreams/72a0a763-fc3e-40b1-a44e-28d0ddaea606/download |
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| identifier.url.fl_str_mv | http://hdl.handle.net/10400.11/6097 |
| instacron_str | ipcb |
| institution | Instituto Politécnico de Castelo Branco |
| instname_str | Instituto Politécnico de Castelo Branco |
| language | eng |
| network_acronym_str | ripcb |
| network_name_str | Repositório Científico do Instituto Politécnico de Castelo Branco |
| oai_identifier_str | oai:repositorio.ipcb.pt:10400.11/6097 |
| organization_str_mv | urn:organizationAcronym:ipcb |
| person_str_mv | Rubio, Eva Masero Dionísio, Rogério Pais Dionísio, Rogério Pais https://www.ciencia-id.pt/2F1A-414F-368B 2F1A-414F-368B http://orcid.org/0000-0002-6810-2447 0000-0002-6810-2447 Torres, Pedro Torres, Pedro https://www.ciencia-id.pt/2711-E707-519C 2711-E707-519C http://orcid.org/0000-0003-4835-5022 0000-0003-4835-5022 |
| publishDate | 2019 |
| publisher.none.fl_str_mv | Springer |
| reponame_str | Repositório Científico do Instituto Politécnico de Castelo Branco |
| repository_id_str | urn:repositoryAcronym:ripcb |
| service_str_mv | urn:repositoryAcronym:ripcb |
| spelling | engSpringerpt_PTThe present paper describes the state of the art related to IIoT Devices and Cyber-Physical systems and presents a use case related to predictive maintenance. Industry 4.0 is the boost for smart manufacturing and demands flexibility and adaptability of all devices/machines in the shop floor. The machines must become smart and interact with other machines inside and outside the industries/factories. The predictive maintenance is a key topic in this industrial revolution. The reason is based on the idea that smart machines must be capable to automatically identify and predict possible faults and actuate before they occur. Vibrations can be problematic in electrical motors. For this reason, we address an experimental study associated with an automatic classification procedure, that runs in the smart devices to detect anomalies. The results corroborate the applicability and usefulness of this machine learning algorithm to predict vibration faults.application/pdfpt_PTIndustrial IoT devices and cyber-physical production systems: review and use caseRubio, Eva MaseroPersonalDionísio, Rogério PaisDSpacehttp://dspace.org/items/fa3cfc92-0ec0-412b-9441-d657fc131926DSpacehttp://dspace.org/items/fa3cfc92-0ec0-412b-9441-d657fc131926PAIS DIONÍSIOROGÉRIOCiência IDhttps://www.ciencia-id.pt2F1A-414F-368BORCIDhttp://orcid.org0000-0002-6810-2447PersonalTorres, PedroDSpacehttp://dspace.org/items/9d9ad49f-3c45-4a99-be21-7f13965c2628DSpacehttp://dspace.org/items/9d9ad49f-3c45-4a99-be21-7f13965c2628BAPTISTA TORRESPEDRO MIGUELCiência IDhttps://www.ciencia-id.pt2711-E707-519CORCIDhttp://orcid.org0000-0003-4835-5022Scopus Author IDhttps://www.scopus.com56261515100HostingInstitutionOrganizationalRepositório Científico do Instituto Politécnico de Castelo Brancoe-mailmailto:repositorio@ipcb.ptrepositorio@ipcb.ptISBNIsPartOf978-3-319-91334-6DOIIsPartOf0.1007/978-3-319-91334-6_402020-12-31T01:30:21Z20192019-01-01T00:00:00ZHandlehttp://hdl.handle.net/10400.11/6097http://purl.org/coar/access_right/c_abf2open accessCyber-physical systemsIndustrial IoTSmart factoriesMachine learningPredictive maintenance275393 bytesliteraturehttp://purl.org/coar/resource_type/c_3248book parthttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorio.ipcb.pt/bitstreams/72a0a763-fc3e-40b1-a44e-28d0ddaea606/downloadLecture Notes in Electrical Engineering505292298 |
| spellingShingle | Industrial IoT devices and cyber-physical production systems: review and use case Rubio, Eva Masero Cyber-physical systems Industrial IoT Smart factories Machine learning Predictive maintenance |
| subject.fl_str_mv | Cyber-physical systems Industrial IoT Smart factories Machine learning Predictive maintenance |
| title | Industrial IoT devices and cyber-physical production systems: review and use case |
| title_full | Industrial IoT devices and cyber-physical production systems: review and use case |
| title_fullStr | Industrial IoT devices and cyber-physical production systems: review and use case |
| title_full_unstemmed | Industrial IoT devices and cyber-physical production systems: review and use case |
| title_short | Industrial IoT devices and cyber-physical production systems: review and use case |
| title_sort | Industrial IoT devices and cyber-physical production systems: review and use case |
| topic | Cyber-physical systems Industrial IoT Smart factories Machine learning Predictive maintenance |
| topic_facet | Cyber-physical systems Industrial IoT Smart factories Machine learning Predictive maintenance |
| url | http://hdl.handle.net/10400.11/6097 |
| visible | 1 |