5502683
doi
10.1109/CBI52690.2021.10050
oai:zenodo.org:5502683
user-dimofac-project
user-eu
Monireh Pourjafarian
German Research Center for Artificial Intelligence (DFKI)
Leon Simar
VDL Industrial Modules
Robert Wilterdink
TNO
Towards a Comprehensive Methodology for Modelling Submodels in the Industry 4.0 Asset Administration Shell
Cornelis Bouter
TNO
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Industry 4.0, asset administration shell, submodel, methodology, immaterial asset, entity-relationship diagram, knowledge representation
<p>The Industry 4.0 Asset Administration Shell is designed as a digital communication interface that exposes information of various aspects of an asset in Submodels, which are functional blocks. However, a methodology that identifies the set of Submodels required for a specific use case is lacking. This work, therefore, presents two results: 1) the methodology we developed to identify the Submodels applicable in a use case and 2) an example application involving immaterial process assets. Our approach complements existing procedures by beginning with a functional description rather than an established standard and by creating a potentially interconnected set of Submodels rather than a singleton. The outcomes were verified by domain experts and through the integration of the corresponding AASs.</p>
This paper is supported by the European Union's Horizon 2020 research and innovation programme under grant agreement No 870092, project DIMOFAC (Digital Intelligent MOdular FACtories).
Zenodo
2021-09-01
info:eu-repo/semantics/conferencePaper
5502682
user-dimofac-project
user-eu
award_title=Digital Intelligent MOdular FACtories; award_number=870092; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/870092; funder_id=00k4n6c32; funder_name=European Commission;
1639554159.178722
1124912
md5:bfd78920b05c415049bb95631656f68b
https://zenodo.org/records/5502683/files/VDLpaper_Preprint.pdf
public