Data integration remains a major challenge in the industry due to the heterogeneity of systems, data sources, and communication protocols. As the Asset Administration Shell becomes a widely adopted standard for digital representations, there is an increasing need for dynamic and user-friendly data integration solutions tailored to it. Existing methods often require extensive programming knowledge, which limits accessibility and slows down deployment. This work presents a low-code approach to industrial data integration based on the Asset Administration Shell, leveraging the standardized Asset Interfaces Description and Asset Interfaces Mapping Configuration submodels, and following an Extract, Transform, Load process. We introduce a Python-based extractor that reads metadata from Asset Interfaces Description and Asset Interfaces Mapping Configuration submodels to automatically generate Node-RED flows with minimal user input. This approach enables real-time data exchange by configuring communication nodes and mappings without manual programming. Overall, our work lowers the barriers to industrial data integration, empowers non-technical users to configure and deploy integration workflows more efficiently, and fosters interoperability through standardized data models.

The Asset Administration Shell is emerging as the standardized digital twin representation for Industrie 4.0 assets, enabling interoperability across organizational and technical boundaries. However, existing access control mechanisms fail to satisfy the Asset Administration Shell’s needs for fine-grained, context-aware, cross-domain security. This paper proposes an access control concept tailored to the Asset Administration Shell, combining Role Based Access Control and Attribute Based Access Control to meet a set of ten key requirements derived from standards, literature, and expert interviews. Our approach follows a technology-neutral architecture, with a concrete prototype implementation using Keycloak as identity provider, Envoy for request interception, and Open Policy Agent for centralized policy based decision-making; thereby separating security concerns from application logic. An evaluation against the defined requirements shows that this prototype meets nine of the ten requirements. Overall, this concept lays the groundwork for future development of secure, scalable, and flexible access control solutions in industrial Asset Administration Shell deployments.

This paper presents a novel approach for the semantic comparison of Asset Administration Shells (AAS), i.e., digital twins within the context of Industry 4.0. As digital twins gain importance in optimizing industrial processes, ensuring interoperability and accurate versioning of AAS becomes critical. We propose a method that focuses on object model-level comparisons rather than mere syntactic differences, enabling a more meaningful assessment of semantic equivalence. Our findings highlight the challenges associated with traditional comparison methods and suggest a comprehensive framework for enhancing AAS versioning and integrity verification.

The integration of diverse data sources into Asset Administration Shell (AAS) is a cornerstone for the advancement of digital twin technologies in industrial ecosystems. To ensure proper data integration, a concept should meet the requirements related to data integration as well as those related to AAS. This study compares three key data integration concepts for AAS-BaSyx Python SDK, BaSyx DataBridge, and the standardized descriptive approach through Asset Interfaces Description (AID) & Asset Interfaces Mapping Configuration (AIMC) submodels. To evaluate the advantages and limitations of each concept, this study employs 12 distinct criteria, assessing how effectively each concept aligns with these criteria. The result provides insights into the unique features of each concept, informing stakeholders about optimal strategies. This study suggests a synergistic approach that combines the advantages of the various methodologies, thereby overcoming individual limitations and enhancing the digital twin ecosystems.

As Industrie 4.0 (I4.0) technologies continue to advance, ensuring the reliability and robustness of emerging standards like Asset Administration Shells (AAS) becomes paramount. This paper introduces a comprehensive testing approach for reactive (a.k.a. Type 2) AAS implementations, addressing the challenges posed by their intricate and dynamic nature. Our methodology adopts a design-by-contract approach to formalize API behavior. We design the client as a test oracle, where code contracts extensively validate the AAS operations, their interactions and effects. The related test cases cover various operation chains, including superpaths, service specifications, and serialization modifiers. The objective of this approach is to enhance the reliability and effectiveness of testing in the evolving landscape of AAS Type 2 implementations.

Current discourse of communicative features of Asset Administration Shells (AAS) leaves an important aspect unaddressed: Should submodels be designed to be usable independently from their overarching AAS? Permitting such independent usage allows for more flexible physical deployment of individual AAS submodels in computer networks or on information media. In this paper, a presentation and classification of possible deployment variants is given, based on this principle. In addition, different requirements on the AAS infrastructure are discussed and how the deployment variants can contribute to their fulfillment. Finally, possible prioritization of infrastructure requirements and resulting submodel deployment are shown in three concrete usage scenarios.

This paper introduces a high-level language compiler with IEC 61131–3 compliance capable of converting control function code written in Python into structured text. The Python-to-Structured Text Compiler aims to bridge the gap between modern language programming and PLC programming in industrial automation. The proposed Py2ST Compiler workflow includes parsing, transformation, code generation, and code import stages. The implementation of these phases is presented in this paper. And the compilation ability of the Py2ST Compiler is validated by a case study. Utilizing the Py2ST Compiler facilitates the development of PLC control functions within the Python environment. This capability enables the management of both IT and OT functions within a unified environment, enhancing the overall project's maintainability and reducing the development cycle.

Asset Administration Shells are an essential component of Industry 4.0, and submodels are crucial to their functioning. However, the current method of generating submodels involves writing custom code, which can lead to code duplication and inconsistencies across submodels. To address these challenges, we propose an automatic generation of submodel-specific classes with predefined meta-information based on submodel templates. Our proposed solution aims to reduce code duplication, provide support in integrated development environments, ensure consistency across submodels, and facilitate the immediate publishing of submodel software development kits. This paper discusses the current approaches for instantiating submodels and their problems, the proposed approach, its requirements, advantages, and an outlook.

The Asset Administration Shell offers the capabilities for unified and interoperable data exchange across the entire life-cycle of an asset. Therefore, using Asset Administration Shells as a data layer is a practical option for facilitating the exchange of information in Simulation-based Engineering. The feasibility of this approach is demonstrated through an implementation, showing that incorporating the Asset Administration Shell as a data layer for standardized data exchange can yield significant benefit for the Simulation-based Engineering process.

The contribution addresses the challenge of transforming a general recipe, which lacks knowledge about specific production resources, into a plant-specific master recipe in the process industry. The authors propose an approach using the concept of capabilities in manufacturing, enabled by an ontology and the Asset Administration Shell. The approach aligns required and offered capabilities at different description levels to allocate equipment to process elements and generate a master recipe in BatchML. The validation of the approach is accompanied by a procedure logic for a modular plant and discusses open challenges. In conclusion, the provided approach offers a methodical and less experience-dependent derivation of a master recipe for a manufacturing process.

The Asset Administration Shell is the key concept for the exchange of asset information in Industrie 4.0 across the entire life cycle of an asset. Therefore, the Asset Administration Shell acts as the central interface to access asset information, which is stored in different source systems, e.g. databases or control units. To achieve this vision, this paper presents the requirements for the standardized integration of data from these source systems into Asset Administration Shell applications and a generic concept for easy and vendor-independent applicability. The concept is demonstrated with two example implementations and evaluated against the requirements.

The digital twin, or more precisely the Asset Administration Shell, is the key element for interoperability in Industrie 4.0. Together with the asset, it forms the I4.0 component. For the development of I4.0 components, the availability of suitable software development tools is becoming increasingly relevant. However, it is not yet specified how these tools are to be systematically tested for correctness, compliance and conformity. These topics are the focus of this work. We show different established testing methods, evaluate their suitability and describe an approach for a capable test environment.

In the scope of Industry 4.0 (I40), one goal is the standardized access to asset information and asset services using standardized submodels (submodel templates) in the Asset Administration Shell. Since submodel templates are modeled by different groups of people, the same asset information will be contained in several submodel templates. For automatic generation of new submodels based on existing information from other submodels, model transformation can be a solution. Therefore, in this contribution, we present a guideline on how to develop a new model transformation language for a given use case and apply this guideline to the concrete use case (model transformation for Asset Administration Shells). As a result, we define of the abstract syntax of a customized model transformation language called AASMTL.

OPC Unified Architecture is one of the leading technologies to realize the horizontal and vertical communication from enterprise layer down to the field layer in automation technology. It defines an address space model consisting of nodes and references without specifying how to store these. Therefore, this paper first describes the concept of a nodestore and a nodestore switch. The core contribution of the nodestore switch is the decoupling of OPC UA servers from their node storage. Based on this, four usage scenarios demonstrate how to utilize the concept to address different requirements, like performance and persistence, the integration of domain specific (proprietary) meta models, the adaptation at runtime and sharing of information models. For each usage scenario a prototypical implementation is described to show an exemplary realization and to gather a deeper understanding of the usage.