Industrial Future How Digital Twins And 3D Streaming Are Sustainably Transforming the Industry

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Digital twins and 3D streaming open up new opportunities in the industry by elevating data management and collaboration to a new level. These technologies are thus changing the way modern processes are designed.

Christian Stein is CEO & Co-Founder of Threedy GmbH.

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 to training. The technology promises greater efficiency, higher precision, a broader range of applications, and increased productivity with fewer errors. The foundation is data, specifically progressive, hyper-connected data, which is stored in a distributed manner. They originate, for example, from the Internet of Things (IoT) or systems like CAD and PLM (Product Lifecycle Management). This shifts the central focus in industrial production away from CAD towards the visualization of connected 3D data.

Challenges in Using Industrial 3D Data

The status quo in the use of industrial 3D data still corresponds to the 1990s. Complex 3D models must first be laboriously exported from their original systems in the form of documents or converted for exchange, thus requiring long download and loading times, offering poor visualization performance, and collaboration takes place accordingly via email, PowerPoint, or screenshots. In addition, dozens of different proprietary formats and thousands of tools exist. For broader use, 3D data often has to be exported from its "single source of truth," resulting in correspondingly inferior output: there is a lack of data quality and depth, and metadata related to components is often completely lost.

Ultimately, with an incorrect focus on aesthetics and immersion, the data depth is further reduced. However, for the industrial end-user, this data depth is precisely what is relevant, as it is the only way to implement typical applications such as DMU (Digital Mock-Ups) or immersive mixed-reality applications in design or aftersales and service. Instead, the accurate assignment of data and its informational depth are particularly important. Another challenge lies in the fact that 3D data and the associated metadata often do not correspond with information from other third-party systems. For example, the integration of CAD and ERP information often fails solely due to different nomenclatures for individual components and groups. This makes the integration of information 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 handling this heterogeneity is sensible, instead of aiming for format-based standardization. The solution lies in virtualizing or abstracting 3D data and its processing and streaming it "on demand." Live links then lead to the data sources of the original systems. Threedy GmbH, a spin-off of the Fraunhofer Institute for Computer Graphics Research (IGD) in Darmstadt (Germany), has developed the visual computing infrastructure component Instant 3D Hub over the past ten years. In collaboration with renowned car manufacturers such as BMW and Mercedes-Benz, this development aims to process and display 3D data more efficiently and seamlessly.

The approach is comparable to standard software for web-based applications such as Google Maps: the information is not stored 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 being made possible with industrial 3D data for a wide range of application areas.

Integration of Data Without Changing the Single Source of Truth

It's not about pre-harmonizing data or standardizing the data storage base to create yet another platform as a "single source of truth." Instead, the goal is to enable and accelerate the consumption of data in any 3D and mixed reality applications. The data remains unchanged in the source systems. No copies are generated, and no separate preparation for specific solutions takes place. Explicit conversions and uploads are eliminated. Instead, the merging of all data formats creates a true multi-CAD environment, allowing users with different CAD systems to collaborate, for example, to speed up the exchange of data and ideas during various development phases. Long loading times—up to 20 minutes or more for complex models—are eliminated, as rendering happens in real-time within a few seconds, and the current model data can be worked on at any time. This enables live collaboration without separate data provisioning.

Such a system, which allows networking and consumption at the latest possible moment, provides the flexibility to make complex, distributed 3D data available to users. The user can work in virtual data spaces tailored to their work situation—having all necessary information immediately at hand, across data types, storage formats, and system boundaries. The 3D data space is available to any applications in parallel: whether it be R&D, engineering, marketing and sales, manufacturing, quality assurance, operations, or after-sales.

Digital Twin

Standardization And Interoperability as Cornerstones of Digital Transformation

Dynamic Information Provision for Work Instructions

A classic use case in the industrial environment with augmented reality involves work instructions. Visualization in 3D enables a high level of detail as well as better understanding and faster information acquisition. This is essential, as components are becoming increasingly smaller and it is often not immediately apparent where they are located or where a specific tool needs to be applied. Additionally, there is the variety of vehicle configurations and machine variants, for example. This variability in production results in enormous volumes of data for the instructions, which not only have to be generated but also stored and made available to the employee.

For example, a major automobile manufacturer from southern Germany is the first in the world to use original CAD data for real-time 3D models and AR in service. This ensures that a digital twin of the respective configuration is always available—including interactive work instructions. The worker scans the vehicle identification number (VIN) and receives a work instruction tailored precisely to the data status of the car they are working on. The basis is the original parts list. This provides the full quality of the information created in design and engineering to generate dynamic work instructions—perfectly matched to the respective situation, from the worker to the service. The employee receives the necessary information immediately. They no longer need to laboriously search for it in pre-published documents or load it onto a device, as the work instruction is no longer historical information produced at an earlier point in time. The interactive work instruction reduces the effort required for the generation and preparation of documentation materials and the publication process. Work processes can thus be carried out with higher quality and fewer errors.

This seamlessly connects to further training and upskilling: the worker does not need to be trained in all possible manufacturing scenarios and various product variants. Through interactive guidance, they learn directly in practice on the respective tasks. This reduces training efforts, and the provisioning process for the instructions can be automated. Efforts for data integration, publication, updating, storage in data management systems, their maintenance, and a search function are eliminated.

Factory of the Future

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 dynamically available in real time. The virtual factory can simulate how changes will affect operations. Long-term data collection in production allows identifying the causes of problems, for instance, when damages such as scratches occur on a specific model or at a specific time. Cluster-related issues, such as error frequencies, can be particularly clearly visualized through so-called heatmaps in the 3D model. This virtual representation of production requires high data dynamics: the overall volume of data is so substantial that companies must know precisely which information they need and how this can be networked end-to-end for automation.

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 environments 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 in terms of compliance and documentation.

A Challenge that Brings Great Opportunities

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 greater efficiency and reduced efforts. For this, technology is needed that enables flexible data integration and 3D data streaming: for maximum flexibility, timeliness, and dynamism.