Adapter module for self-learning production systems

Detalhes bibliográficos
Autor(a) principal: Di Orio, Giovanni
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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spelling 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
dc.rights.driver.fl_str_mv 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
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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