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Astract: Es gibt zahlreiche Publikationen, die die digitale Transformation im Tief- und Tunnelbau propagieren. Als Lösungsansatz wird dabei immer wieder Building Information Modeling (BIM) genannt und die Umsetzung der digitalen Transformation basierend auf dieser Methodik gefordert. Der prototypische Charakter eines Tunnelbauprojekts erschwert jedoch eine standardisierte Vorgehensweise. Hinzu kommt, dass die beteiligten Fachdisziplinen für unterschiedliche Gewerke individuelle Softwaretools mit proprietären (nicht standardisierten) Datenformaten nutzen. Durch diese in sich geschlossenen Datenmodelle ist eine offene BIM Arbeitsweise (Open BIM) nur schwer zu realisieren. Das hat der Lehrstuhl für Subsurface Engineering an der Montanuniversität Leoben zum Anlass genommen und zwei anwendungsorientierte Forschungsprojekte zur digitalen Transformation im Tief- und Tunnelbau lanciert, deren Inhalte in diesem Artikel kurz vorgestellt werden. Das „Zentrum am Berg (ZaB)“ dient in beiden Projekten als zentrale Infrastruktur zu Evaluierungszwecken.

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Astract: Variability is crucial in the design of many advanced goods and it is also receiving increasing attention in production systems engineering. Since OPC Unified Architecture plays an important role when it comes to standardized information exchange in modern production systems, it can be a melting pot for information from various engineering domains, such as product design and production engineering - thus, it is an ideal place to hold variability information of products and production systems alike. Based on an initial variability information model we propose additional concepts for the persisting of configurations.

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Astract: Model-driven engineering (MDE) provides tools and methods for the manipulation of formal models. In this letter, we leverage MDE for the transformation of production system models into flat files that are understood by general purpose planning tools and that enable the computation of "plans", i.e., sequences of production steps that are required to reach certain production goals. These plans are then merged back into the production system model, thus enriching the formalized production system knowledge.

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Astract: Smart production systems need to be able to adapt to changing environments and market needs. They have to reflect changes in (i) the reconfiguration of the production systems themselves, (ii) the processes they perform or (iii) the products they produce. Manual intervention for system adaptation is costly and potentially error-prone. In this article, we propose a model-driven approach for the automatic generation and regeneration of production plans that can be triggered anytime a change in any of the three aforementioned parameters occurs.

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Astract: AutomationML provides a versatile modeling environment for the description of production systems. However, when starting a new AutomationML project, or when serializing existing data with the AutomationML format, there are no rules on how to structure these models in a meaningful way. In this work, we present an approach for structuring AutomationML models, based on the IEC 62264 standard. In our approach we are implementing the process of serializing IEC 62264 information declaratively, by leveraging the power of model transformations, as they are applied in the context of model-driven (software) engineering.