On-demand Shared Digital Twins – An Information Architectural Model to Create Transparency in Collaborative Supply Networks

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dc.contributor.authorCirullies, Jan
dc.contributor.authorSchwede, Christian
dc.date.accessioned2020-12-24T19:19:26Z
dc.date.available2020-12-24T19:19:26Z
dc.date.issued2021-01-05
dc.description.abstractIndustrial companies already apply digital twins for the digital representation of the physical world. In addition, information sharing becomes increasingly decisive for the competition, e.g. in supply networks where products and logistics data such as demands and capacities are exchanged. As many companies are, however, highly reluctant to share data across the supply chain, this paper applies the methodology of design science research to, first, state the requirements for shared digital twins based on five industrial use cases. It turns out that with regard to data decentralism, sovereignty and compatibility through global standardization are key success factors. Hence, second, this paper presents a concept for a shared digital twin providing data on demand, i.e. at the right time and in particular with data condensed to the concrete need, thus, minimizing volume. The concept covers both the company-internal and the supply network perspective.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2021.202
dc.identifier.isbn978-0-9981331-4-0
dc.identifier.urihttp://hdl.handle.net/10125/70814
dc.language.isoEnglish
dc.relation.ispartofProceedings of the 54th Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectModeling and Decision Making in Manufacturing and Logistics in the Age of Industry 4.0
dc.subjectdata sovereignty
dc.subjectdecentral
dc.subjectdigital twin
dc.subjectontology
dc.subjectsupply chain
dc.titleOn-demand Shared Digital Twins – An Information Architectural Model to Create Transparency in Collaborative Supply Networks
prism.startingpage1675

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Modeling and Decision Making in Manufacturing and Logistics in the Age of Industry 4.0