Implementing digital transformation collaboratively

Part one: Industry 4.0 and digital twins

Industry 4.0-or the Fourth Industrial Revolution-involves harnessing technology to automate industry and manufacturing. An important concept in Industry 4.0 is the digital twin, which lets you build digital models of your assets, processes, or products.

For several years, Fraunhofer IESE, NetApp^®, and objective partner have been working closely together on Industry 4.0 solutions. Since Hannover Messe 2019, these partners have offered a joint Industry 4.0 middleware solution: ShopFloor 4.0. The open-source software Eclipse BaSyx forms the core of ShopFloor 4.0, and as a specialist in on-premises and cloud-based data services, NetApp provides the data infrastructure.

The digital twin

The term 'digital twin' is used in various contexts with different meanings. It ranges from a simple 3D model of a physical object (asset) to a full digital description of an asset, including physical simulation models and access to the real asset. Either way, it's a digital proxy of a real asset. The term 'digital twin' is often used to refer to either a model, a digital shadow, or a true digital twin. But according to Kritzinger et al., these three terms reflect the different degrees of integration between real asset and virtual description:

• Model: a digital representation-for example, a pure simulation model, without automated exchange between real and digital object
• Digital shadow: an asset model that includes an automated flow of information from reality into the virtual representation
• Digital twin: a digital shadow with feedback of changes from virtual mapping to reality and the ability to influence or control a real system

The digital twin addresses an aspect that many systems lack today: Even if entire systems or components are already digitized, there is no uniform digital image of these systems in their entirety. This problem was precisely the original motivation for creating the digital twin.2 The goal was to create a virtual representation that could be tested instead of a real system to save development costs. This representation would behave like its real counterpart in every situation. Even today, with the complexity and diversity of current systems, testing efforts lead to challenges that are difficult to solve without digital system mappings.

The advantages of digital system mappings in industry

Here's an example. In manufacturing engineering, changes to production are often tested on real systems. But this testing means that you must halt ongoing production. If errors occur, you must eliminate them before restarting production with the changed configuration. These downtimes are expensive and significantly decrease the flexibility of production.

Digital system mapping would solve both problems. In production, you could test changes on a digital image of the system before modifying the real system. You'd end up finding the majority of problems in the virtual environment, which would reduce downtime, costs, and overall time.

Originally, the digital twin was conceived to virtualize expensive tests in the aerospace industry.² Today, the automotive industry, among others, also uses digital twins to reduce development costs through virtual testing.

The documentation of production processes

The digital twin concept is mostly firmly established in the field of automation technology. During production, the individual production steps and product quality must be accurately documented. Especially in critical systems-for example, in automotive and aerospace industries-digital shadows are used to make workpieces traceable. The digital shadow of a product stores not only the current state, but also the history of production. If you couldn't digitize production systems that automatically assign measured forces to the correct product, such fine-grained documentation would be unthinkable.

You can also use digital shadows to realize digital images of production processes and manufacturing equipment. Collecting and providing data makes it possible to identify optimization potential and to use predictive maintenance to avoid unplanned downtime. The virtual commissioning of production lines and manufacturing plants is also becoming more important. In this process, you check software configurations and modifications on a plant's digital twins before you apply them to the real plant.

Smart city implementation

Pilot projects for smart cities, such as those in Stockholm and Singapore, develop digital shadows by digitizing and integrating plans, maps, and building and sensor data to create digital images of cities. Digital shadows are used, for example, to virtually test infrastructure decisions and traffic concepts. They're also used to involve citizens more directly in decision-making processes; digital shadows make these processes transparent, which can increase their acceptance.

In conclusion

Digital images are already being used in many areas and represent an important basis for future systems. There are many solutions for models and digital shadows, but solutions for true digital twins are rare.

With other partners from research and industry, Fraunhofer IESE has developed the Industry 4.0 middleware solution ShopFloor 4.0 under the name Eclipse BaSyx. ShopFloor 4.0 implements the principles of the digital twin with the Industry 4.0 asset administration shell standard.

If you're interested in more detail on what an Industry 4.0 infrastructure can look like, we recommend the white paper Industry 4.0 Made Easy. And we'll write more about Eclipse BaSyx, asset administration shells, and integration into your data fabric architecture in our future blog posts.

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