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2024
Journal Article
Title
Concept of Event-based AAS Transformation Engine
Abstract
The Asset Administration Shell (AAS) is the backbone of the Industry 4.0 movement. It provides an implementation concept for the Digital Twin and is a solution for the challenges of interoperability on the shop floor. The principle of storing multiple data models - so-called submodels - describing a distinct aspect of an asset enables information exchange between hardware and software. To support the development, standardization, and maintenance of AAS submodels, this work presents a concept for an event-based AAS transformation engine. The vision of the engine is to create submodels based on properties of already existing submodels but with a different structure. The scope of this work is outlined by collecting abstract use cases and requirements regarding different viewpoints of the engine: model transformation in general, interaction with the AAS environment, and functions of the engine. Based on this work, a data model for transformation rules is developed. The data model focuses on how to address submodels in an AAS environment and how a submodel transformation can be described as a list of basic transformation actions. In order to provide horizontal scalability, a software architecture is developed based on the service-oriented design principle. Therefore, the model transformation task is split into basic sub-tasks. Each sub-task has a corresponding software service type that handles the specific task. As the architecture allows parallel read and write threads in an AAS environment, an access lock mechanism is introduced to avoid interference between the services. The data model and software architecture provide the foundation for an event-based transformation engine. For future work, the concept will be implemented and tested in a real-world use case to provide feedback for the next development iteration.
Conference
Open Access
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Rights
CC BY-NC-ND 4.0: Creative Commons Attribution-NonCommercial-NoDerivatives
Additional link
Language
English