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

2025-12-17

AI Summary

Current Asset Administration Shells (AAS) in manufacturing digital twins are predominantly static, lacking dynamic service integration and adaptive capabilities. To address this, this paper proposes an active AAS architecture that innovatively embeds containerized services within AAS submodels, enabling runtime, on-demand deployment and autonomous behavioral extension via an event-driven mechanism. The architecture integrates OPC UA for industrial communication, RAMI 4.0 for standardized modeling, and Docker for lightweight, portable service execution—ensuring both interoperability and executability. Evaluated on a three-axis milling machine case study, the proposed architecture transforms the AAS from a passive data container into an active service execution interface. This significantly improves system responsiveness and enables AI-driven intelligent evolution. The work provides a concrete pathway toward the “executable twin” paradigm in digital twin systems.

Technology Category

• Multiagent Systems: Agent/AI Theories and Architectures
• Cognitive Modeling & Cognitive Systems: Agent Architectures
• Intelligent Robots: Embodied AI

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems

Abstract

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.

Problem

• Enabling dynamic service integration in static Asset Administration Shells
• Integrating executable containerized services into digital twin models
• Transforming passive digital twins into proactive, adaptive systems

Innovation

• Container-based architecture for dynamic AAS integration
• Event-driven submodel extension enabling proactive service deployment
• Modular design supporting runtime adaptation of digital twins