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.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:77609 |
| Date | 27 January 2022 |
| Creators | Ulmer, Jessica, Mostafa, Youssef, Wollert, Jörg |
| Contributors | Hochschule für Technik, Wirtschaft und Kultur Leipzig |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | German |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:conferenceObject, info:eu-repo/semantics/conferenceObject, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 978-3-910103-00-9, urn:nbn:de:bsz:l189-qucosa2-775789, qucosa:77578 |
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