Carsten Ellwein | Searcharxiv

arXiv2026

Software-heavy Asset Administration Shells: Classification and Use Cases

The Asset Administration Shell (AAS) is an emerging technology for the implementation of digital twins in the field of manufacturing. Software is becoming increasingly important, not only in general but specifically in relation to manufacturing, especially with regard to digital manufacturing and a shift towards the usage of artificial intelligence. This increases the need not only to model software, but also to integrate services directly into the AAS. The existing literature contains individual solutions to implement such software-heavy AAS. However, there is no systematic analysis of software architectures that integrate software services directly into the AAS. This paper aims to fill this research gap and differentiate architectures based on software quality criteria as well as typical manufacturing use cases. This work may be considered as an interpretation guideline for software-heavy AAS, both in academia and for practitioners.

cs.SE↗

arXiv2025

A Container-based Approach For Proactive Asset Administration Shell Digital Twins

In manufacturing, digital twins, realized as Asset Administration Shells (AAS), have emerged as a prevalent practice. These digital replicas, often utilized as structured repositories of asset-related data, facilitate interoperability across diverse systems. However, extant approaches treat the AAS as a static information model, lacking support for dynamic service integration and system adaptation. The existing body of literature has not yet thoroughly explored the potential for integrating executable behavior, particularly in the form of containerized services, into or from the AAS. This integration could serve to enable proactive functionality. In this paper, we propose a submodel-based architecture that introduces a structured service notion to the AAS, enabling services to dynamically interact with and adapt AAS instances at runtime. This concept is implemented through the extension of a submodel with behavioral definitions, resulting in a modular event-driven architecture capable of deploying containerized services based on embedded trigger conditions. The approach is illustrated through a case study on a 3-axis milling machine. Our contribution enables the AAS to serve not only as a passive digital representation but also as an active interface for executing added-value services.%, thereby laying the foundation for future AI-driven adaptation and system-level intelligence in digital twin environments.

cs.SE↗