Adapter module for self-learning production systems
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Data de Publicação: | 2013 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10362/10402 |
Resumo: | Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica, Sistemas e Computadores |
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Adapter module for self-learning production systemsAgile manufacturingContext awarenessData miningSOADissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica, Sistemas e ComputadoresThe dissertation presents the work done under the scope of the NP7 Self-Learning project regarding the design and development of the Adapter component as a foundation for the Self-Learning Production Systems (SLPS). This component is responsible to confer additional proprieties to production systems such as lifecycle learning, optimization of process parameters and, above all, adaptation to different production contexts. Therefore, the SLPS will be an evolvable system capable to self-adapt and learn in response to dynamic contextual changes in manufacturing production process in which it operates. The key assumption is that a deeper use of data mining and machine learning techniques to process the huge amount of data generated during the production activities will allow adaptation and enhancement of control and other manufacturing production activities such as energy use optimization and maintenance. In this scenario, the SLPS Adapter acts as a doer and is responsible for dynamically adapting the manufacturing production system parameters according to changing manufacturing production contexts and, most important, according to the history of the manufacturing production process acquired during SLPS run time.To do this, a Learning Module has been also developed and embedded into the SLPS Adapter. The SLPS Learning Module represents the processing unit of the SLPS Adapter and is responsible to deliver Self-learning capabilities relying on data mining and operator’s feedback to up-date the execution of adaptation and context extraction at run time. The designed and implemented SLPS Adapter architecture is assessed and validated into several application scenario provided by three industrial partners to assure industrial relevant self-learning production systems. Experimental results derived by the application of the SLPS prototype into real industrial environment are also presented.Faculdade de Ciências e TecnologiaOliveira, JoséCândido, GonçaloRUNDi Orio, Giovanni2013-09-13T10:01:51Z20132013-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/10402TID:201764237enginfo: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:RCAAP2024-03-11T03:44:09Zoai:run.unl.pt:10362/10402Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:19:27.315829Repositório 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 |
Adapter module for self-learning production systems |
title |
Adapter module for self-learning production systems |
spellingShingle |
Adapter module for self-learning production systems Di Orio, Giovanni Agile manufacturing Context awareness Data mining SOA |
title_short |
Adapter module for self-learning production systems |
title_full |
Adapter module for self-learning production systems |
title_fullStr |
Adapter module for self-learning production systems |
title_full_unstemmed |
Adapter module for self-learning production systems |
title_sort |
Adapter module for self-learning production systems |
author |
Di Orio, Giovanni |
author_facet |
Di Orio, Giovanni |
author_role |
author |
dc.contributor.none.fl_str_mv |
Oliveira, José Cândido, Gonçalo RUN |
dc.contributor.author.fl_str_mv |
Di Orio, Giovanni |
dc.subject.por.fl_str_mv |
Agile manufacturing Context awareness Data mining SOA |
topic |
Agile manufacturing Context awareness Data mining SOA |
description |
Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica, Sistemas e Computadores |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-09-13T10:01:51Z 2013 2013-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10362/10402 TID:201764237 |
url |
http://hdl.handle.net/10362/10402 |
identifier_str_mv |
TID:201764237 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Faculdade de Ciências e Tecnologia |
publisher.none.fl_str_mv |
Faculdade de Ciências e Tecnologia |
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reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799137837904297984 |