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Data-driven Knowledge-Based Engineering Supported by the Digital Twin

Power Transformer production at Efacec is unsuitable with Industry 4.0 trends since information is not shared efficiently abroad for stakeholders to make better decisions. Creative and high-value stakeholders spend their time on low-value repetitive tasks and fail to implement authentic innovation practices.
Moreover, during the lifecycle of a Power Transformer, a large amount of data is generated, from its concept, design, manufacturing, and operation until disposal. The difficulty is that the current product design and engineering processes are not designed to take advantage of the rich data available through implementing the Digital Twin concept and their potential for knowledge extraction.
In this context, this work aims to study how the availability of data and information provided through the Digital Twin approach will impact product design and engineering processes. Information and data analytical methods become valuable components in organisations, enabling knowledge dissemination and collaboration among stakeholders to address better performance in developing new customisable products.
Considering the features proposed for the Power Transformer during a product's lifecycle, there is a complementarity between Knowledge-Based Engineering and Digital Twin. The latter serves as a support platform for Knowledge-Based Engineering processes. It comes particularly from Digital Twin's ability to act as a recommendation system, storing and providing information that assists the engineer in defining functional requirements and conforming them to the project's objectives.
The case study research method was employed as an empirical inquiry. This method is an appropriate research design when it is necessary to obtain holistic, concrete, contextual, and in-depth knowledge about a specific real-world subject's key characteristics, meanings, and implications.
Achieving the research aims will contribute to assessing the impact on product design and engineering processes of the availability of data and information provided through the Digital Twin. The organisation will then have conditions to reach a new context characterised by volatile processes, whose trends and customers change rapidly, demanding custom yet fast design approaches.

Identiferoai:union.ndltd.org:up.pt/oai:repositorio-aberto.up.pt:10216/143030
Date25 July 2025
CreatorsSthefan Gabriel Berwanger
ContributorsFaculdade de Engenharia
Source SetsUniversidade do Porto
LanguageEnglish
Detected LanguageEnglish
TypeDissertação
Formatapplication/pdf
RightsembargoedAccess, https://creativecommons.org/licenses/by/4.0/

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