Inconsistency management in heterogeneous engineering data in intralogistics based on coupled metamodels

Titel in Übersetzung: Inkonsistenz Management in heterogenen Engineering Daten in der Intralogistik auf Basis von gekoppelten Metamodellen

Fan Ji, Maximilian Wünnenberg, Rafael Schypula, Juliane Fischer, Dominik Hujo, Michael Goedicke, Johannes Fottner, Birgit Vogel-Heuser

Publikation: Beitrag in FachzeitschriftArtikelBegutachtung

1 Zitat (Scopus)

Abstract

During the development of intralogistics systems (ILS), heterogeneous models are created, which represent discipline-specific views, e.g., control software developed by automation engineers or discrete-event simulation models created by simulation engineers. These models represent discipline-specific views on the system but contain overlapping information. Thereby, keeping the information in different development models consistent is challenging and currently requires high manual effort, which highly depends on the developers' experience. To overcome this challenge, an approach to link heterogeneous model data and identify potential information inconsistencies within and between models automatically is proposed. The concept is evaluated with a use case containing three typical inconsistencies from five representative engineering models applied in ILS development.

Titel in ÜbersetzungInkonsistenz Management in heterogenen Engineering Daten in der Intralogistik auf Basis von gekoppelten Metamodellen
OriginalspracheEnglisch
Seiten (von - bis)364-379
Seitenumfang16
FachzeitschriftAt-Automatisierungstechnik
Jahrgang71
Ausgabenummer5
DOIs
PublikationsstatusVeröffentlicht - 1 Mai 2023

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