Machine learning in supply chain management

Detalhes bibliográficos
Autor(a) principal: Hoppe, Magnus Tilmar
Data de Publicação: 2019
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10362/69191
Resumo: Almost every day newspapers and online media publish articles about the ongoing development of machine learning and related applications. Eventually, the practical use cases seem infinite and the potential especially for the efficient organization of supply chains is difficult to determine. This paper examines different applications as well as the underlying operating principles of self-learning algorithms in order to derive implications for supply chain management. Furthermore, an outlook for the prospective development of machine learning and the related further establishment of cognitive automation will be presented.
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spelling Machine learning in supply chain managementMachine learningSupply chain managementPredictive maintenanceCognitive automationDomínio/Área Científica::Ciências Sociais::Economia e GestãoAlmost every day newspapers and online media publish articles about the ongoing development of machine learning and related applications. Eventually, the practical use cases seem infinite and the potential especially for the efficient organization of supply chains is difficult to determine. This paper examines different applications as well as the underlying operating principles of self-learning algorithms in order to derive implications for supply chain management. Furthermore, an outlook for the prospective development of machine learning and the related further establishment of cognitive automation will be presented.Carvalho, José Crespo deRUNHoppe, Magnus Tilmar2019-05-10T10:36:27Z2019-01-152019-01-15T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/69191TID:202223760enginfo: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:RCAAP2024-03-11T04:32:49Zoai:run.unl.pt:10362/69191Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:34:55.498236Repositório 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 Machine learning in supply chain management
title Machine learning in supply chain management
spellingShingle Machine learning in supply chain management
Hoppe, Magnus Tilmar
Machine learning
Supply chain management
Predictive maintenance
Cognitive automation
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short Machine learning in supply chain management
title_full Machine learning in supply chain management
title_fullStr Machine learning in supply chain management
title_full_unstemmed Machine learning in supply chain management
title_sort Machine learning in supply chain management
author Hoppe, Magnus Tilmar
author_facet Hoppe, Magnus Tilmar
author_role author
dc.contributor.none.fl_str_mv Carvalho, José Crespo de
RUN
dc.contributor.author.fl_str_mv Hoppe, Magnus Tilmar
dc.subject.por.fl_str_mv Machine learning
Supply chain management
Predictive maintenance
Cognitive automation
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Machine learning
Supply chain management
Predictive maintenance
Cognitive automation
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description Almost every day newspapers and online media publish articles about the ongoing development of machine learning and related applications. Eventually, the practical use cases seem infinite and the potential especially for the efficient organization of supply chains is difficult to determine. This paper examines different applications as well as the underlying operating principles of self-learning algorithms in order to derive implications for supply chain management. Furthermore, an outlook for the prospective development of machine learning and the related further establishment of cognitive automation will be presented.
publishDate 2019
dc.date.none.fl_str_mv 2019-05-10T10:36:27Z
2019-01-15
2019-01-15T00:00:00Z
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/10362/69191
TID:202223760
url http://hdl.handle.net/10362/69191
identifier_str_mv TID:202223760
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.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
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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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