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Data-Centric Engineering (Online), 2022-01, Vol.3, Article e33
2022

Details

Autor(en) / Beteiligte
Titel
An approach for system analysis with model-based systems engineering and graph data engineering
Ist Teil von
  • Data-Centric Engineering (Online), 2022-01, Vol.3, Article e33
Ort / Verlag
Cambridge: Cambridge University Press
Erscheinungsjahr
2022
Link zum Volltext
Quelle
Elektronische Zeitschriftenbibliothek (Open access)
Beschreibungen/Notizen
  • Abstract Model-based systems engineering (MBSE) aims at creating a model of a system under development, covering the complete system with a level of detail that allows to define and understand its behavior and enables to define any interface and work package based on the model. Once the model is established, further benefits can be reaped, such as the analysis of complex technical correlations within the system. Various insights can be gained by displaying the model as a formal graph and querying it. To enable such queries, a graph schema is necessary, which allows to transfer the model into a graph database. In the course of this paper, we discuss the design of a graph schema and MBSE modeling approach, enabling deep going system analysis and anomaly resolution in complex embedded systems with a focus on testing and anomaly resolution. The schema and modeling approach are designed to answer questions such as What happens if there is an electrical short in a component? Which other components are now offline and which data cannot be gathered anymore? If a component becomes unresponsive, which alternative routes can be established to obtain data processed by it. We build on the use case of qualification and operations of a small spacecraft. Structural elements of the MBSE model are transferred to a graph database where analyses are conducted on the system. The schema is implemented by means of an adapter for MagicDraw to Neo4J. A selection of complex analyses is shown in the example of the MOVE-II space mission.
Sprache
Englisch
Identifikatoren
ISSN: 2632-6736
eISSN: 2632-6736
DOI: 10.1017/dce.2022.33
Titel-ID: cdi_doaj_primary_oai_doaj_org_article_e8579dfdf60941e79d75a97fa2d48de4

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