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From Engineering Models to Digital Twins: Generating AAS from SysML v2 Models
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.ORCID iD: 0000-0003-3683-8174
Johannes Kepler University Linz, Linz, Austria.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-8027-0611
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1687-930X
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2025 (English)In: Journal of Systems and Software, ISSN 01641212, Vol. 233, article id 112688Article in journal (Refereed) Published
Abstract [en]

Context: Digital twins serve as virtual representations of systems, enabling capabilities such as intelligent monitoring, real-time control, decision-making, and predictive analytics. The Asset Administration Shell (AAS) is the pivotal Industry 4.0 standard for digital twin engineering. In parallel, the Systems Modeling Language (SysML) has emerged as a modeling standard for systems engineering, providing a formalized and semantically rich approach to system modeling. SysML v2 is its recent evolution. With its growing adoption, multiple models are expected to be widely available, each capturing different facets of the modeled system by leveraging diverse engineering capabilities offered by various tool ecosystems. Problem: Instead of manually re-creating models for digital twinning, existing system models should be leveraged to relieve repetitive modeling tasks. While SysML v2 and AAS are prominent standards in DT engineering, they lack direct integration, necessitating a dedicated approach for their seamless interoperability. Purpose: This paper presents a practical investigation into the conceptual alignment between the SysML v2 and AAS specifications, with a focus on their structural and behavioral modeling aspects. It proposes an implementable approach for mapping SysML v2 to AAS, enabling the automated generation of AAS models from SysML v2 models. Method: To realize this approach, we employ model-driven engineering techniques leveraging the Eclipse Modeling Framework (EMF) and model transformations based on the Query View Transformation (QVT) language. The proposed model transformation incorporates query mechanisms for extracting structured elements, preserving information and structural integrity, and ensuring static semantic consistency at design-time and seamless integration between the two investigated standards. We develop and validate the model transformation following an iterative test-driven development approach using an existing set of 24 SysML v2 examples, sourced from the official SysML v2 repository. Result: We deliver a QVT-based, EMF-compliant transformation that automatically generates AAS submodel templates from SysML v2 models, preserving structural hierarchies and behavioral semantics via dedicated AAS concepts and their extension. Through an iterative, test-driven development process, we validate metamodel conformance, information preservation, and structural integrity. The current mapping addresses design-time concepts, and the implementation supports forward transformation. All conceptual mappings, QVT scripts, and example artifacts are publicly available in a dedicated repository.

Place, publisher, year, edition, pages
Elsevier BV , 2025. Vol. 233, article id 112688
Keywords [en]
Digital Twin; SysML v2; Asset Administration Shell; Interoperability; Model-Driven Engineering; Model Transformation
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-71172DOI: 10.1016/j.jss.2025.112688ISI: 001632367800001Scopus ID: 2-s2.0-105023655522OAI: oai:DiVA.org:mdh-71172DiVA, id: diva2:1952519
Available from: 2025-04-15 Created: 2025-04-15 Last updated: 2025-12-29Bibliographically approved
In thesis
1. Facilitating Interoperability for Digital Twins
Open this publication in new window or tab >>Facilitating Interoperability for Digital Twins
2025 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The digital twin concept has emerged as a pivotal tool in digital transformation, offering digital representations of physical components, systems, or processes to enable remote monitoring and control. The functional suitability of digital twins relies on interoperable subsystems that can seamlessly and effectively exchange data. Consequently, achieving interoperability in digital twin solutions is crucial. However, this remains an open challenge due to the diversity of data models employed across existing digital twin implementations. This challenge is further intensified by the lack of practical methods to integrate early-phase engineering models with digital twin models.This thesis provides software architecture analysis of digital twins, using the ISO 23247 standard as a baseline, and highlights the limitations of current interoperability solutions—drawing on findings from systematic studies, industry surveys, and expert interviews.In addition, it addresses the identified limitations by progressively developing a solution rooted in model-driven engineering, and the Asset Administration Shell standard, supporting the development of more scalable and standardized digital twins.The proposed approach aims to automate the integration process between engineering models and digital twin models, eliminating the need for manual creation of transformation rules. A full-scale implementation has been realized using model transformations to automatically generate Asset Administration Shell-compliant models from artifacts described in Systems Modeling Language version 2. The approach is developed and validated following an iterative, test-driven development methodology through the translation of a representative set of Systems Modeling Language version 2 models into Asset Administration Shell models, demonstrating its feasibility, completeness, and correctness.

Place, publisher, year, edition, pages
Västerås: Mälardalens universitet, 2025
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 432
National Category
Software Engineering
Research subject
Computer Science
Identifiers
urn:nbn:se:mdh:diva-71173 (URN)978-91-7485-708-5 (ISBN)
Public defence
2025-06-17, Gamma och via Zoom, Mälardalens universitet, Västerås, 09:15 (English)
Opponent
Supervisors
Available from: 2025-04-15 Created: 2025-04-15 Last updated: 2025-10-10Bibliographically approved

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Ferko, EnxhiBucaioni, AlessioBehnam, Moris

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