Open AccessDigital Twin Academy
Author(s) -
Jessica Ulmer,
Youssef Mostafa,
Jörg F. Wollert
Publication year - 2022
Language(s) - English
Resource type - Conference proceedings
DOI - 10.33968/2022.33
Subject(s) - computer science , persona , focus (optics) , selection (genetic algorithm) , key (lock) , work (physics) , path (computing) , point (geometry) , knowledge management , multimedia , human–computer interaction , engineering , artificial intelligence , mechanical engineering , physics , computer security , optics , programming language , geometry , mathematics
Digital twins are seen as one of the key technologies of Industry 4.0. Although many research groups focus on digital twins and create meaningful outputs, the technology has not yet reached a broad application in the industry. The main reasons for this imbalance are the complexity of the topic, the lack of specialists, and the unawareness of the twin opportunities. The project 'Digital Twin Academy' aims to overcome these barriers by focusing on three actions: Building a digital twin community for discussion and exchange, offering multi-stage training for various knowledge levels, and implementing realworld use cases for deeper insights and guidance. In this work, we focus on creating a flexible learning platform that allows the user to select a training path adjusted to personal knowledge and needs. Therefore, a mix of basic and advanced modules is created and expanded by individual feedback options. The usage of personas supports the selection of the appropriate modules.