Enhancing AI Assets with Asset Administration Shells (AAS) in AI Lifecycle and MLOps

Description of the service

Transform Your AI Assets into Asset Administration Shells!

The Asset Administration Shell (AAS) supports standard-compliant data exchange along the entire production lifecycle and is used to implement the digital twin. Submodels are also being developed for AI/ML use cases and the AI lifecycle, which can already be used experimentally. However, the integration and management of assets from OT and IT in AI/ML applications and along an AI lifecycle is complex and dynamic. In addition, AI assets like models, data and development, and operational knowledge are available in heterogeneous structures and need adaptation or migration for various AI/ML setups.

We evaluate the use of AI submodels for your assets and offer you an experimental environment with an MLOps integration. This enables you to test and demonstrate the integration of your assets along the AI lifecycle based on the AAS standard.
Expected results: Report with experimentation results and recommendations
The methodology: Experimentation with AI-targeted submodels such as „Artificial Intelligence Dataset“, „Artificial Intelligence Deployment“, „Artificial Intelligence Model Nameplate“, while ensuring conformity to the AAS specifications (part 1, 2, 5), the AAS submodel specifications. There is also access to an MLOps experimental environment.
Target: Manufacturers or companies that want to use AAS for their systems in future. AI/ML system providers or integrators for Production Systems and Industrial Manufacturing.

Improve your project
around production and
automation with AI technologies