Knowledge-Based Engineering supported by the Digital-Twin: the case of the Power Transformer at EFACEC

Detalhes bibliográficos
Autor(a) principal: Miguel Alves de Azevedo
Data de Publicação: 2020
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/128587
Resumo: Industry 4.0 has made it possible for emerging technologies to revolutionize how organizations operate. New applications, supported by the Internet of things, cyber physical systems, and cloud computing, take advantage of large data exchange networks that capture data from the real and virtual world, to generate valuable insights for product development. This, together with the growing digitalization of product lifecycle information, has made information the most valuable asset of an organization, as it can be applied to improve product design, reduce lead time and decrease monetary costs. However, the growing volume, formats, and purposes of the information an organization captures, also brings challenges for information management, and consequently, appropriate IM and KM instruments and strategies must be adopted to successfully take advantage of organizational knowledge. The adoption of Knowledge-based Engineering can accomplish these goals. KBE refers to the knowledge management tasks of capturing, storing, modeling, coding, and sharing of organizational knowledge, both in explicit form, such as documents, and tacit form, present in the minds of employees. Ultimately, this results in systems that can automate design tasks. Also in the context of technological advances, a new concept called Digital Twin has emerged, which employs bidirectional data transmission to mirror the lifecycle of a physical product, in the virtual realm. Proposed DT functionalities actively use organizational knowledge to improve and automate product design, and as such, this technology can be an adequate vessel for KBE. This dissertation focuses on the implementation of the Digital Twin in power transformer development processes. Using the case of Efacec, a portuguese firm of the energy sector, the DT concept was developed, and this involved defining functionalities that are driven by organizational knowledge to automate, optimize, and streamline PT design tasks, thus accomplishing the goal of KBE. Some of the proposed DT features are the generation of design templates, the identification of design non-conformities, and the capture of engineer feedback. Furthermore, the DT information architecture that is required for these functionalities to successfully be implemented, was envisioned, by defining all captured and generated information in each PT lifecycle phase. Finally, a faceted classification scheme that classifies DT information and enables queries within the DT platform, was developed.
id RCAP_f48a52b772d3dc961162c9eef634c50d
oai_identifier_str oai:repositorio-aberto.up.pt:10216/128587
network_acronym_str RCAP
network_name_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository_id_str 7160
spelling Knowledge-Based Engineering supported by the Digital-Twin: the case of the Power Transformer at EFACECCiências da computação e da informaçãoComputer and information sciencesIndustry 4.0 has made it possible for emerging technologies to revolutionize how organizations operate. New applications, supported by the Internet of things, cyber physical systems, and cloud computing, take advantage of large data exchange networks that capture data from the real and virtual world, to generate valuable insights for product development. This, together with the growing digitalization of product lifecycle information, has made information the most valuable asset of an organization, as it can be applied to improve product design, reduce lead time and decrease monetary costs. However, the growing volume, formats, and purposes of the information an organization captures, also brings challenges for information management, and consequently, appropriate IM and KM instruments and strategies must be adopted to successfully take advantage of organizational knowledge. The adoption of Knowledge-based Engineering can accomplish these goals. KBE refers to the knowledge management tasks of capturing, storing, modeling, coding, and sharing of organizational knowledge, both in explicit form, such as documents, and tacit form, present in the minds of employees. Ultimately, this results in systems that can automate design tasks. Also in the context of technological advances, a new concept called Digital Twin has emerged, which employs bidirectional data transmission to mirror the lifecycle of a physical product, in the virtual realm. Proposed DT functionalities actively use organizational knowledge to improve and automate product design, and as such, this technology can be an adequate vessel for KBE. This dissertation focuses on the implementation of the Digital Twin in power transformer development processes. Using the case of Efacec, a portuguese firm of the energy sector, the DT concept was developed, and this involved defining functionalities that are driven by organizational knowledge to automate, optimize, and streamline PT design tasks, thus accomplishing the goal of KBE. Some of the proposed DT features are the generation of design templates, the identification of design non-conformities, and the capture of engineer feedback. Furthermore, the DT information architecture that is required for these functionalities to successfully be implemented, was envisioned, by defining all captured and generated information in each PT lifecycle phase. Finally, a faceted classification scheme that classifies DT information and enables queries within the DT platform, was developed.2020-07-172020-07-17T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/10216/128587TID:202598497engMiguel Alves de Azevedoinfo: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:RCAAP2023-11-29T12:49:17Zoai:repositorio-aberto.up.pt:10216/128587Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:27:27.559799Repositório 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 Knowledge-Based Engineering supported by the Digital-Twin: the case of the Power Transformer at EFACEC
title Knowledge-Based Engineering supported by the Digital-Twin: the case of the Power Transformer at EFACEC
spellingShingle Knowledge-Based Engineering supported by the Digital-Twin: the case of the Power Transformer at EFACEC
Miguel Alves de Azevedo
Ciências da computação e da informação
Computer and information sciences
title_short Knowledge-Based Engineering supported by the Digital-Twin: the case of the Power Transformer at EFACEC
title_full Knowledge-Based Engineering supported by the Digital-Twin: the case of the Power Transformer at EFACEC
title_fullStr Knowledge-Based Engineering supported by the Digital-Twin: the case of the Power Transformer at EFACEC
title_full_unstemmed Knowledge-Based Engineering supported by the Digital-Twin: the case of the Power Transformer at EFACEC
title_sort Knowledge-Based Engineering supported by the Digital-Twin: the case of the Power Transformer at EFACEC
author Miguel Alves de Azevedo
author_facet Miguel Alves de Azevedo
author_role author
dc.contributor.author.fl_str_mv Miguel Alves de Azevedo
dc.subject.por.fl_str_mv Ciências da computação e da informação
Computer and information sciences
topic Ciências da computação e da informação
Computer and information sciences
description Industry 4.0 has made it possible for emerging technologies to revolutionize how organizations operate. New applications, supported by the Internet of things, cyber physical systems, and cloud computing, take advantage of large data exchange networks that capture data from the real and virtual world, to generate valuable insights for product development. This, together with the growing digitalization of product lifecycle information, has made information the most valuable asset of an organization, as it can be applied to improve product design, reduce lead time and decrease monetary costs. However, the growing volume, formats, and purposes of the information an organization captures, also brings challenges for information management, and consequently, appropriate IM and KM instruments and strategies must be adopted to successfully take advantage of organizational knowledge. The adoption of Knowledge-based Engineering can accomplish these goals. KBE refers to the knowledge management tasks of capturing, storing, modeling, coding, and sharing of organizational knowledge, both in explicit form, such as documents, and tacit form, present in the minds of employees. Ultimately, this results in systems that can automate design tasks. Also in the context of technological advances, a new concept called Digital Twin has emerged, which employs bidirectional data transmission to mirror the lifecycle of a physical product, in the virtual realm. Proposed DT functionalities actively use organizational knowledge to improve and automate product design, and as such, this technology can be an adequate vessel for KBE. This dissertation focuses on the implementation of the Digital Twin in power transformer development processes. Using the case of Efacec, a portuguese firm of the energy sector, the DT concept was developed, and this involved defining functionalities that are driven by organizational knowledge to automate, optimize, and streamline PT design tasks, thus accomplishing the goal of KBE. Some of the proposed DT features are the generation of design templates, the identification of design non-conformities, and the capture of engineer feedback. Furthermore, the DT information architecture that is required for these functionalities to successfully be implemented, was envisioned, by defining all captured and generated information in each PT lifecycle phase. Finally, a faceted classification scheme that classifies DT information and enables queries within the DT platform, was developed.
publishDate 2020
dc.date.none.fl_str_mv 2020-07-17
2020-07-17T00:00:00Z
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 https://hdl.handle.net/10216/128587
TID:202598497
url https://hdl.handle.net/10216/128587
identifier_str_mv TID:202598497
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
instacron_str RCAAP
institution RCAAP
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
_version_ 1799135580992307201