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Article type: Research Article
Authors: Voss, Christophera; * | Petzold, Frankb | Rudolph, Stephana
Affiliations: [a] Institute of Aircraft Design, University of Stuttgart, Germany | [b] Chair for Architectural Informatics, Leonhard Obermeyer Center, Munich Data Science Institute, Technical University of Munich, Germany
Correspondence: [*] Corresponding author. Email: [email protected].
Note: [1] The present paper represents an extended version of the conference paper by Voss, C., Petzold, F., & Rudolph, S. (2020) “Linking building design and the digital factory by graph-based design languages”. In Digital proceedings of TMCE 2020, TMCE 2020 repository (p. 515-528). Retrieved from tmce.io.tudelft.nl/proceedings
Abstract: In engineering, design decisions in one domain exhibit multiple consequences in other domains. These consequences result from the often more or less hidden coupling between the different design domains. In order to examine these consequences, models need to be created. In practice, this is challenging due to the exchange of data between different engineering domains, since different software applications are often used and the effort involved with manual model creation. In this paper, we explore the use of graph-based design languages in a Model-Based Systems Engineering (MBSE) approach to link the digital factory with building design. We also show that the use of a common formal representation based on the Unified Modeling Language (UML) supports the interoperability between the two domains. Finally, we demonstrate how the engineering knowledge for the preliminary design of a factory building can be formally described using graph-based design languages and how the production line of the digital factory can then be used as an input to automatically create valid preliminary designs for the factory building.1
Keywords: Graph-based design languages, model-based systems engineering, digital factory, building design, knowledge-based engineering
DOI: 10.3233/JID200019
Journal: Journal of Integrated Design and Process Science, vol. 24, no. 3-4, pp. 95-120, 2020
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