Interoperable data extraction and information enrichment system to support smart manufacturing: an experimental application on CNC machining lines of a healthcare product
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Production |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132022000100804 |
Resumo: | Abstract Paper aims This research develops an expert system for interoperable data acquirement and information enrichment in the manufacturing lines of a healthcare product, ensuring the correct data and information sharing and supporting the decision-making process. Originality The research contributes to creating and developing a novel method of knowledge representation that systematises the data collection and creates semantic relationships that allow the analysis of the productive performance of healthcare product manufacturing through semantic rules and inference engines. Research method The Interoperable Data Extraction and Information Enrichment system 4.0 (IDEIEs 4.0) was developed using an ontological approach and experimentally applied in an implantable Vascular Access Catheterindicated production process, which involves a machining controlling process. Main findings The developed system application pointed out the reduction of human mistakes in the data collecting, errors in the production control and data loss due to the digital automatic and interoperable collection process that brings precision in data collection and security in their storage. Implications for theory and practice The solution presented here can be used as a starting point for new directions of research to support the decision-making process with extra and formalised information, improving product quality, flexibilities the manufacturing process and reducing the time wasted. |
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Interoperable data extraction and information enrichment system to support smart manufacturing: an experimental application on CNC machining lines of a healthcare productIndustry 4.0Healthcare ProductData CollectingSemantic InteroperabilityMachiningAbstract Paper aims This research develops an expert system for interoperable data acquirement and information enrichment in the manufacturing lines of a healthcare product, ensuring the correct data and information sharing and supporting the decision-making process. Originality The research contributes to creating and developing a novel method of knowledge representation that systematises the data collection and creates semantic relationships that allow the analysis of the productive performance of healthcare product manufacturing through semantic rules and inference engines. Research method The Interoperable Data Extraction and Information Enrichment system 4.0 (IDEIEs 4.0) was developed using an ontological approach and experimentally applied in an implantable Vascular Access Catheterindicated production process, which involves a machining controlling process. Main findings The developed system application pointed out the reduction of human mistakes in the data collecting, errors in the production control and data loss due to the digital automatic and interoperable collection process that brings precision in data collection and security in their storage. Implications for theory and practice The solution presented here can be used as a starting point for new directions of research to support the decision-making process with extra and formalised information, improving product quality, flexibilities the manufacturing process and reducing the time wasted.Associação Brasileira de Engenharia de Produção2022-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132022000100804Production v.32 2022reponame:Productioninstname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPRO10.1590/0103-6513.20210058info:eu-repo/semantics/openAccessHelena,Sofia TononCamargo,Victória Romaguera SilvaAmaral,Thomas Victor BelfortSzejka,Anderson LuisLeite,Athon Francisco Curi Staben de MouraCanciglieri,Matheus Beltrameeng2022-04-20T00:00:00Zoai:scielo:S0103-65132022000100804Revistahttps://www.scielo.br/j/prod/https://old.scielo.br/oai/scielo-oai.php||production@editoracubo.com.br1980-54110103-6513opendoar:2022-04-20T00:00Production - Associação Brasileira de Engenharia de Produção (ABEPRO)false |
dc.title.none.fl_str_mv |
Interoperable data extraction and information enrichment system to support smart manufacturing: an experimental application on CNC machining lines of a healthcare product |
title |
Interoperable data extraction and information enrichment system to support smart manufacturing: an experimental application on CNC machining lines of a healthcare product |
spellingShingle |
Interoperable data extraction and information enrichment system to support smart manufacturing: an experimental application on CNC machining lines of a healthcare product Helena,Sofia Tonon Industry 4.0 Healthcare Product Data Collecting Semantic Interoperability Machining |
title_short |
Interoperable data extraction and information enrichment system to support smart manufacturing: an experimental application on CNC machining lines of a healthcare product |
title_full |
Interoperable data extraction and information enrichment system to support smart manufacturing: an experimental application on CNC machining lines of a healthcare product |
title_fullStr |
Interoperable data extraction and information enrichment system to support smart manufacturing: an experimental application on CNC machining lines of a healthcare product |
title_full_unstemmed |
Interoperable data extraction and information enrichment system to support smart manufacturing: an experimental application on CNC machining lines of a healthcare product |
title_sort |
Interoperable data extraction and information enrichment system to support smart manufacturing: an experimental application on CNC machining lines of a healthcare product |
author |
Helena,Sofia Tonon |
author_facet |
Helena,Sofia Tonon Camargo,Victória Romaguera Silva Amaral,Thomas Victor Belfort Szejka,Anderson Luis Leite,Athon Francisco Curi Staben de Moura Canciglieri,Matheus Beltrame |
author_role |
author |
author2 |
Camargo,Victória Romaguera Silva Amaral,Thomas Victor Belfort Szejka,Anderson Luis Leite,Athon Francisco Curi Staben de Moura Canciglieri,Matheus Beltrame |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Helena,Sofia Tonon Camargo,Victória Romaguera Silva Amaral,Thomas Victor Belfort Szejka,Anderson Luis Leite,Athon Francisco Curi Staben de Moura Canciglieri,Matheus Beltrame |
dc.subject.por.fl_str_mv |
Industry 4.0 Healthcare Product Data Collecting Semantic Interoperability Machining |
topic |
Industry 4.0 Healthcare Product Data Collecting Semantic Interoperability Machining |
description |
Abstract Paper aims This research develops an expert system for interoperable data acquirement and information enrichment in the manufacturing lines of a healthcare product, ensuring the correct data and information sharing and supporting the decision-making process. Originality The research contributes to creating and developing a novel method of knowledge representation that systematises the data collection and creates semantic relationships that allow the analysis of the productive performance of healthcare product manufacturing through semantic rules and inference engines. Research method The Interoperable Data Extraction and Information Enrichment system 4.0 (IDEIEs 4.0) was developed using an ontological approach and experimentally applied in an implantable Vascular Access Catheterindicated production process, which involves a machining controlling process. Main findings The developed system application pointed out the reduction of human mistakes in the data collecting, errors in the production control and data loss due to the digital automatic and interoperable collection process that brings precision in data collection and security in their storage. Implications for theory and practice The solution presented here can be used as a starting point for new directions of research to support the decision-making process with extra and formalised information, improving product quality, flexibilities the manufacturing process and reducing the time wasted. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-01-01 |
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=S0103-65132022000100804 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-65132022000100804 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/0103-6513.20210058 |
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 |
Associação Brasileira de Engenharia de Produção |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia de Produção |
dc.source.none.fl_str_mv |
Production v.32 2022 reponame:Production instname:Associação Brasileira de Engenharia de Produção (ABEPRO) instacron:ABEPRO |
instname_str |
Associação Brasileira de Engenharia de Produção (ABEPRO) |
instacron_str |
ABEPRO |
institution |
ABEPRO |
reponame_str |
Production |
collection |
Production |
repository.name.fl_str_mv |
Production - Associação Brasileira de Engenharia de Produção (ABEPRO) |
repository.mail.fl_str_mv |
||production@editoracubo.com.br |
_version_ |
1754213154896740352 |