IoT Platforms and Hardware Integrations for Industry 4.0 Applications
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Data de Publicação: | 2019 |
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Tipo de documento: | Artigo de conferência |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1109/ICIIS47346.2019.9063256 http://hdl.handle.net/11449/198790 |
Resumo: | The concept of Industry 4.0 (I4.0) or the 4th Industrial Revolution, formulated in Germany, now spreading through the world, challenges the existing manufacturing industry to adopt new standards to increase productivity and save resources through the Internet of Thing (IoT) platforms. Adaptation of I4.0 has been sluggish due to lack of training and skill. Engineers and technicians need new skills, related hardware and software solutions to transform Industry 3.0 (I3.0) manufacturing facilities to I4.0 facility. Machines in I4.0 factory are cyber-physical systems with capabilities to make their own decisions based on data collected via cloud-based IoT platforms. These platforms consist of data subscribers and publishers and are analyzed through machine learning algorithms. This paper describes available technologies to implement I4.0 in a manufacturing facility, using Energy Management 4.0 as an example. The smart factory must reach a certain maturity related energy management. The technology presented in this paper helps to achieve some maturity level without spending high initial investments. These technologies are also applicable to realize economic savings in other aspects of I4.0. |
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IoT Platforms and Hardware Integrations for Industry 4.0 ApplicationsIndustry 4.0Internet of ThingsThe concept of Industry 4.0 (I4.0) or the 4th Industrial Revolution, formulated in Germany, now spreading through the world, challenges the existing manufacturing industry to adopt new standards to increase productivity and save resources through the Internet of Thing (IoT) platforms. Adaptation of I4.0 has been sluggish due to lack of training and skill. Engineers and technicians need new skills, related hardware and software solutions to transform Industry 3.0 (I3.0) manufacturing facilities to I4.0 facility. Machines in I4.0 factory are cyber-physical systems with capabilities to make their own decisions based on data collected via cloud-based IoT platforms. These platforms consist of data subscribers and publishers and are analyzed through machine learning algorithms. This paper describes available technologies to implement I4.0 in a manufacturing facility, using Energy Management 4.0 as an example. The smart factory must reach a certain maturity related energy management. The technology presented in this paper helps to achieve some maturity level without spending high initial investments. These technologies are also applicable to realize economic savings in other aspects of I4.0.Purdue University Northwest Department of Engineering TechnologySao Paulo State University (UNESP) Department of Electrical EngineeringSao Paulo State University (UNESP) Department of Electrical EngineeringPurdue University NorthwestUniversidade Estadual Paulista (Unesp)Athula Kulatunga, N.Sampaio, Daniel J. B. S. [UNESP]2020-12-12T01:22:05Z2020-12-12T01:22:05Z2019-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObject209-214http://dx.doi.org/10.1109/ICIIS47346.2019.90632562019 IEEE 14th International Conference on Industrial and Information Systems: Engineering for Innovations for Industry 4.0, ICIIS 2019 - Proceedings, p. 209-214.http://hdl.handle.net/11449/19879010.1109/ICIIS47346.2019.90632562-s2.0-85084149232Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPeng2019 IEEE 14th International Conference on Industrial and Information Systems: Engineering for Innovations for Industry 4.0, ICIIS 2019 - Proceedingsinfo:eu-repo/semantics/openAccess2021-10-22T20:28:28Zoai:repositorio.unesp.br:11449/198790Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T21:51:58.692650Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
IoT Platforms and Hardware Integrations for Industry 4.0 Applications |
title |
IoT Platforms and Hardware Integrations for Industry 4.0 Applications |
spellingShingle |
IoT Platforms and Hardware Integrations for Industry 4.0 Applications Athula Kulatunga, N. Industry 4.0 Internet of Things |
title_short |
IoT Platforms and Hardware Integrations for Industry 4.0 Applications |
title_full |
IoT Platforms and Hardware Integrations for Industry 4.0 Applications |
title_fullStr |
IoT Platforms and Hardware Integrations for Industry 4.0 Applications |
title_full_unstemmed |
IoT Platforms and Hardware Integrations for Industry 4.0 Applications |
title_sort |
IoT Platforms and Hardware Integrations for Industry 4.0 Applications |
author |
Athula Kulatunga, N. |
author_facet |
Athula Kulatunga, N. Sampaio, Daniel J. B. S. [UNESP] |
author_role |
author |
author2 |
Sampaio, Daniel J. B. S. [UNESP] |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Purdue University Northwest Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Athula Kulatunga, N. Sampaio, Daniel J. B. S. [UNESP] |
dc.subject.por.fl_str_mv |
Industry 4.0 Internet of Things |
topic |
Industry 4.0 Internet of Things |
description |
The concept of Industry 4.0 (I4.0) or the 4th Industrial Revolution, formulated in Germany, now spreading through the world, challenges the existing manufacturing industry to adopt new standards to increase productivity and save resources through the Internet of Thing (IoT) platforms. Adaptation of I4.0 has been sluggish due to lack of training and skill. Engineers and technicians need new skills, related hardware and software solutions to transform Industry 3.0 (I3.0) manufacturing facilities to I4.0 facility. Machines in I4.0 factory are cyber-physical systems with capabilities to make their own decisions based on data collected via cloud-based IoT platforms. These platforms consist of data subscribers and publishers and are analyzed through machine learning algorithms. This paper describes available technologies to implement I4.0 in a manufacturing facility, using Energy Management 4.0 as an example. The smart factory must reach a certain maturity related energy management. The technology presented in this paper helps to achieve some maturity level without spending high initial investments. These technologies are also applicable to realize economic savings in other aspects of I4.0. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-12-01 2020-12-12T01:22:05Z 2020-12-12T01:22:05Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/conferenceObject |
format |
conferenceObject |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1109/ICIIS47346.2019.9063256 2019 IEEE 14th International Conference on Industrial and Information Systems: Engineering for Innovations for Industry 4.0, ICIIS 2019 - Proceedings, p. 209-214. http://hdl.handle.net/11449/198790 10.1109/ICIIS47346.2019.9063256 2-s2.0-85084149232 |
url |
http://dx.doi.org/10.1109/ICIIS47346.2019.9063256 http://hdl.handle.net/11449/198790 |
identifier_str_mv |
2019 IEEE 14th International Conference on Industrial and Information Systems: Engineering for Innovations for Industry 4.0, ICIIS 2019 - Proceedings, p. 209-214. 10.1109/ICIIS47346.2019.9063256 2-s2.0-85084149232 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2019 IEEE 14th International Conference on Industrial and Information Systems: Engineering for Innovations for Industry 4.0, ICIIS 2019 - Proceedings |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
209-214 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
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1808129367440621568 |