The BMW Group uses a powerful Digital Twin Registry (DTR) based on Eclipse BaSyx. It helps users to quickly find digital twins in the Catena-X data space and unambiguously map them to the corresponding data sets. Fraunhofer IESE implemented the solution and optimized it, particularly in terms of performance, scalability, and future-proofing.
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What is it about:
Ensuring Digital Twins Can Be Reliably Found in the Catena-X Data Space
The Challenge:
BMW Group Needs a Scalable Digital Twin Registry for Catena-X
The Support:
Fraunhofer IESE provides the Digital Twin Registry with Eclipse BaSyx Go
The Result:
Improved Performance and Scalability for Digital Twins in Catena-X
Digital twins are digital representations of real-world objects, such as vehicles, components, or machines. They form an important foundation for standardized data exchange in industrial data spaces such as Catena-X.
A Digital Twin Registry (DTR) is a digital directory. It makes digital twins discoverable and shows which data sets belong to which digital twin. The DTR does not store the data itself, but rather points to the corresponding digital twins and the associated information.
As the number of vehicles produced annually increases, so do the demands on the registry’s performance and scalability. The DTR must reliably manage large volumes of digital twins and ensure short response times even when handling many concurrent requests. To this end, Fraunhofer IESE examined the existing Tractus-X DTR implementation and compared it with the requirements of the Catena-X and Asset Administration Shell specifications. Based on this analysis, IESE developed an optimized DTR using Eclipse BaSyx Go. Among other features, the solution incorporates detailed access rules and a scalable technical architecture. The results of this development were published as open source on GitHub.
The BMW Group faced the challenge of deploying a Digital Twin Registry that would deliver high performance and be future-proof for use in a highly scalable industrial environment. The large number of vehicles produced annually results in a correspondingly large number of digital twins that must be located and managed via Catena-X. At the same time, the solution must keep pace with the ongoing development of relevant standards, particularly the Asset Administration Shell. In addition to high processing capacity, short response times, system scalability, and reliable operation under heavy load were therefore particularly important. The registry should continue to operate stably even as the number of digital twins and requests continues to rise.
Fraunhofer IESE supported in both the technical analysis and the development and optimization of the Digital Twin Registry.
First, IESE examined the existing Tractus-X DTR implementation in detail. Based on this, IESE developed an optimized DTR using Eclipse BaSyx Go, taking into account the latest Catena-X and AAS specifications, such as AAS v3.2. A particular focus was placed on efficiently processing very large volumes of digital twins. In addition, the solution was designed to scale even as workload increases. To achieve this, additional technical resources can be provisioned without having to redevelop the entire system.
In addition, IESE integrated detailed access rules. These rules allow for the specification of which users or companies are permitted to access specific digital twins or data offerings. IESE provided Helm Charts for use in a Kubernetes environment. These enable the DTR to be installed, operated, and scaled as needed in a standardized and reproducible manner. In addition, IESE analyzed and optimized the new implementation specifically for the relevant Catena-X use cases. Through performance analyses and technical improvements, response times were shortened and potential bottlenecks in requests to the DTR were eliminated. The developed components and improvements were subsequently released as open source on GitHub. This allows other companies and projects within the Eclipse BaSyx and Catena-X ecosystems to utilize and further develop the results.
Optimizing the Digital Twin Registry has laid the groundwork for managing large volumes of digital twins quickly and reliably. The solution can process many requests even under heavy load and is designed to scale as requirements grow.
The implementation, based on Eclipse BaSyx Go, provides a powerful and future-proof foundation for deploying digital twins in the Catena-X data space. The reduced response times facilitate rapid access to digital twins and associated data sets. At the same time, the improvements help prevent timeouts and performance bottlenecks under high load.
The Kubernetes-based deployment enables consistent and flexible operation. As a result, the solution can be more easily adapted to future requirements and increasing data volumes.
The release of the developed components as open source also creates sustainable added value for the entire ecosystem. Other companies and projects can utilize the results and collaborate on further development.
Fraunhofer Institute for Experimental Software Engineering IESE