Digital Twin The Advantages of Virtualizing 3D Data

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3D data streamed for industrial applications has the potential to revolutionize processes: solutions such as digital twins of products or entire factories can be provided with dynamic, always up-to-date data—resulting in better communication, faster and more efficient processes, and fewer errors.

Physical and virtual worlds are increasingly merging in applications such as digital twins. Complex processes can be simulated, monitored, and controlled in real-time. Augmented Reality (AR) enables intuitive visual support for complex tasks—from production to maintenance and training.

The basis is data, more precisely, progressive, hyper-connected data that is maintained in a distributed manner. They come, for example, from the Internet of Things (IoT) or from systems like CAD and PLM. This shifts the central theme in industrial production away from CAD towards the visualization of networked 3D data.

Collaboration Via Email And PowerPoint

The problem with this is that the status quo in the use of industrial 3D data still corresponds to the 1990s. Complex 3D models must first be laboriously extracted or sent for exchange in the form of documents, require long download and loading times, offer poor visualization performance, and collaboration occurs accordingly via email and PowerPoint. In addition, there are dozens of different proprietary formats and thousands of tools. For broader use, 3D data often has to be converted and downgraded, resulting in inferior output: there is a lack of data quality and detail, and metadata related to components often gets completely lost. Ultimately, a wrong focus on optics and immersion further reduces the data quality.

For the industrial end user, it usually does not matter whether a surface shimmers metallically; instead, the precise allocation of the data and its depth of information are particularly relevant. Another difficulty lies in the fact that 3D data is not designed to represent the same quality of information and dynamics outside of the source system (e.g., PLM or CAD). As a result, the merging of information becomes highly complex.

Virtualize And Stream 3D Data

Industrial data is characterized by heterogeneity—there is no single format that can harmonize all information from all data sources. Therefore, an approach that is capable of dealing with this heterogeneity, instead of aiming for a format-based unification, is sensible. The solution is to virtualize 3D data and its processing and stream it "on demand." Live links then lead to the data sources of the original systems.

The approach is comparable to standard software for web-based applications like Google Maps: the information is not stored on the end device but is available as a stream on demand.

For this purpose, Threedy GmbH, a spin-off of the Fraunhofer Institute for Computer Graphics Research (IGD) in Darmstadt (Germany), has developed the visual computing infrastructure component instant3Dhub in collaboration with automotive manufacturers like BMW and Mercedes-Benz over the past 10 years. The approach is comparable to a standard software for web-based applications like Google Maps: the information is not available on the end device but is provided as a stream on demand; the application continuously pulls relevant information based on user interest and dynamically connects the heterogeneous data. This is now possible with industrial 3D data for various application areas.

Single Source of Truth is Maintained

The goal is not to harmonize data in advance or to unify the data storage base and build yet another platform as a "single source of truth." Rather, it is to enable and accelerate the consumption of data in any 3D and mixed reality applications. The data remains in the source systems: no copies are created, and there is no separate preparation for specific solutions; explicit conversions and uploads are eliminated.

Instead, the merging of all data formats results in real multi-CAD, among other things, allowing users with different CAD systems to collaborate to support the exchange of data and ideas at various stages of development. Long loading times are eliminated, the display occurs in real-time in a matter of seconds, and current model data can be worked with at any time. This enables live collaboration without separate data provisioning.

The 3D data space is available to any application simultaneously: be it R&D, engineering, marketing and sales, manufacturing, quality assurance, operations, or after sales.

Such a system, which allows for networking and consumption at the latest possible moment, offers the flexibility to provide complex, distributed 3D data for users: the user can work in virtual data rooms that are adapted to his work situation—he can pull in all necessary information across data types, storage formats, and system boundaries. The 3D data room is available simultaneously to any application: be it R&D, engineering, marketing and sales, manufacturing, quality assurance, operation, or after-sales.

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What Enables Dynamic Information Provision

• A classic use case in the industrial environment with augmented reality is work instructions. Visualization in 3D enables a high level of detail, better understanding, and faster information acquisition. This is necessary as components are becoming smaller and more complex, and it is often not immediately apparent where they are located or where to apply a particular tool. Additionally, there is the variety of, for example, vehicle configurations and variants. This variability results in enormous data volumes for the instructions, which must not only be generated but also maintained and made available to the employee.

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  Date: 08.12.2025

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• Another use case for virtualized 3D data and dynamic information flows is the factory of the future: its digital twin accesses real-time IoT data such as sensor information and combines connectivity with 3D and XR (Extended Reality). The information is available dynamically in real-time. The virtual factory can simulate how changes will affect the system; long-term data collection, for example in production, allows the identification of the causes of problems, such as when damage like scratches occurs on a specific model or at a specific time. Cluster issues like error frequencies are particularly illustrative in the 3D model. This virtual representation of production requires a high level of data dynamism: the total data volume is so high that companies need to know exactly what information they need and how it can be networked for end-to-end automation.

Digital Twin Requires A Lot of Preparation

Such a digital twin therefore requires a lot of groundwork—companies face the challenges of first building competencies, establishing foundational technologies, and bridging the gap between IT and OT (operational technology). There is a lack of technological maturity to serve and network various data sources, especially given different data management worlds and formats. The virtual factory is the future of manufacturing, but it is technically complex and will mean a significant change for the working world—in terms of processes, but also regarding compliance and documentation.

The digital twin can be used as an application not only at all stages of the product lifecycle—from design to manufacturing to after sales—but also to virtualize entire factories. Companies benefit from increased efficiency and reduced efforts.

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