This paper investigates the design of a digital product passport (DPP) model based on the asset administration shell (AAS) framework to support the circular economy while ensuring cross-industry applicability. In a circular economy, resources are continuously reused, fostering more sustainable manufacturing. The European Commission’s initiatives target this issue, with the DPP playing a critical role in sharing product sustainability information, such as product composition and repairability, throughout its lifecycle. However, a widely applicable DPP approach has yet to be established. This study consolidates existing standards, and scientific literature to develop a data model that aligns with circular economy principles. Using the AAS framework initially developed by the Plattform Industrie 4.0, we mapped the data requirements to submodel templates and addressed gaps in the data needed for real-life implementation. The results demonstrate that the proposed DPP data model is specific enough for practical use cases, such as the upcoming EU battery passport, while remaining flexible enough for application across various industries. The AAS framework’s adaptability and comprehensive data exchange capabilities make it a suitable foundation for developing DPPs that support the transition to a circular economy.

Although standards and specifications for digital twins aim to create interoperability in Industry 4.0, each standard has its own goals, focuses and representations for digital twins. This paper examines an approach to increasing interoperability between established digital twin specifications by transformation. Accordingly, several specifications are presented and requirements for transformation are examined. Following the feasibility analysis, a mapping between the Digital Twin Definition Language (DTDL) and Asset Administration Shell (AAS) was created. To examine the feasibility of this approach, the transformation was implemented and tested for a physical asset. This paper demonstrates that a generic mapping between DTDL and AAS can be applied for transformation in use cases where DTDL models are provided while AAS is required.

The concept of digital twins (DT) has already been discussed some decades ago. Digital representations of physical assets are key components in industrial applications as they are the basis for decision making. What is new is the conceptual approach to consider DT as well-defined software entities themselves that follow the whole lifecycle of their physical counterparts from the engineering, operation up to the discharge, and hence, have their own type description, identity, and lifecycle. This paper elaborates on this idea and argues the need for systematic DT engineering and management. After a conceptual description of DT, the paper proposes a DT lifecycle model and presents methodologies and tools for DT management, also in the context of Industrie 4.0 concepts, such as the asset administration shell (AAS), the international data spaces (IDS), and IEC standards (such as OPC UA and AML). As a tool example for the support of DT engineering and management, the Fraunhofer-advanced AAS tools for digital twins (FA³ST) are presented in more detail.

The use of open-source software is crucial for the digitalization of manufacturing, including the implementation of Digital Twins as envisioned in Industry 4.0. This research paper provides a comprehensive comparison of free and open-source implementations of the reactive Asset Administration Shell (AAS) for creating Digital Twins. A structured search on GitHub and Google Scholar was conducted, leading to the selection of four implementations for detailed analysis. Objective evaluation criteria were defined, and a testing framework was created to test support for the most common AAS model elements and API calls. The results show that all implementations support at least a minimal set of required features while none implement the specification in all details, which highlights the challenges of implementing the AAS specification and the incompatibility between different implementations. This paper is therefore the first attempt at a comprehensive comparison of AAS implementations and identifies potential areas for improvement in future implementations. It also provides valuable insights for software developers and researchers in the field of AAS-based Digital Twins.

Industry 4.0 supports the vision of networked machines in decentralized production plants across the value chain. Hence, it requires highly connected partners exchanging relevant data about products, processes, and production resources. This paper proposes the usage of data spaces and digital twins to enable this Industry 4.0 vision and investigates the building blocks to realize a data space for Industry 4.0, e.g., the integration of digital twins inside the data space based upon the latest specification of the Industry 4.0 Asset Administration Shell. A prototypical implementation shows the feasibility of storing product carbon footprints inside a digital twin and sharing it over a data space with other partners.

Digital twins (DTs) based on the Asset Administration Shell (AAS) enable interoperable representations of industrial assets, while dataspaces like those defined by the International Data Spaces (IDS) facilitate sovereign, policy-governed data exchange across organizations. However, integrating AAS-based DTs into dataspaces remains challenging due to manual processes, synchronization issues, and varying implementation strategies. This paper addresses these gaps by first presenting a structured analysis of existing integration approaches and evaluating the user requirements to be met. We then introduce a flexible reference implementation extending the Eclipse Dataspace Connector (EDC), which automates AAS registration into dataspaces. Finally, we conduct a qualitative comparison with state-of-the-art prototypes from initiatives such as Catena-X and Factory-X and demonstrate the application of our integration approach in the MODAI project for sensor-driven manufacturing data sharing. Results indicate that the integration approach reduced manual effort and provides synchronization between digital twins and dataspace.