Interview "The Asset Administration Shell holds far more potential than mere data exchange."

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Open Industry 4.0 Alliance

FAULHABER Drive Systems

Wuxi InfiMotion Technology Co., Ltd.

In the interview, Christian Heinrich and Ekrem Yigitdöl from the Open Industry 4.0 Alliance discuss the key technology digital twin, which enables real-time monitoring and more, but is hindered by challenges such as insufficient standards and data integration issues.

The benefits of digital twins seem to be clear to many people by now. How do you think the use of the technology is progressing in the industrial environment?

Christian Heinrich: First, I would like to emphasize that the term "digital twin" is heavily overloaded and there are different interpretations of what exactly it means. Without engaging in a discussion of the definition here, it can be seen that the use of digital twins in the industrial environment is increasingly developing into a key technology.

The standardized digital twin in the form of the Asset Administration Shell, or AAS for short, offers enormous potential in cross-company data exchange, as all values of the twin are clearly semantically described. Here, adaptation in the market is gradually noticeable, but by no means has it reached everywhere yet.

In the Asset Administration Shell, there is much more potential than just data exchange, as it can also model capabilities, skills, states, events, and rules, so that the AAS of a product to be manufactured contains all the information for production and can independently interact with the AAS of the production facilities via publish-and-subscribe mechanisms. Keyword: Type 3 AAS.

Would you give our readers one or two successful practical examples of the use of such digital twins in the manufacturing industry?

Christian Heinrich: A renowned component manufacturer is restructuring the entire information flow in production so that the digital twin—in the form of the Asset Administration Shell—serves as the backbone. When an order is placed by a customer, the instance AAS is created and enriched with information through the various steps in the company. Each department writes and reads relevant information in the AAS. It states what should be done with the product in each manufacturing step. At the end of production, a minimized AAS, without internal company information, is delivered with the manufactured product to the customer, who can then easily integrate it into their own systems.

Another example is also a component manufacturer that writes its end-of-line test results into the AAS of this very asset and makes them available to the customer after purchasing the product. The customer can purchase smart services for the products, which can now configure themselves instance-specifically based on these test results.

This is just the beginning of the development. We will see an AAS of the product to be manufactured in production that independently triggers actions and not just holds information. This will have a significant impact, especially for the production of batch size 1, even when it takes place across companies, for instance, with regard to the concept of Manufacturing as a Service, or MaaS for short.

That sounds promising but is not yet widely used. What is generally still lacking at the moment?

Christian Heinrich: Currently, the biggest hurdle is still the dissemination of standards for digital twins. However, some companies are still hesitant to invest in the establishment of new standards in their production, as they are waiting to see if these will prevail in the long term. They are looking for investment security before undertaking extensive implementations.

For more complex use cases, there are also no established best practices for how these should be modeled within the framework of the AAS. This can make implementation difficult, as companies are uncertain about how to optimally implement specific scenarios.

A central argument for the introduction of the AAS is the semantic interoperability of the data as well as the clear structuring of this information. While many companies recognize the added value of this data clarity, they also know that implementation is often associated with considerable effort. However, this effort is not exclusively related to the technology of the AAS itself, but to the preliminary work that each company must undertake to present its data consistently and cleanly. This groundwork is necessary to subsequently map the data in a format such as the AAS.

However, the actual implementation of digital twins still proves to be a challenge for many companies. Why is that?

Christian Heinrich: Several reasons can be cited for this. Firstly, the effective use of digital twins requires extensive integration of data from various sources, such as individual sensors, machines, and different heterogeneous and distributed IT systems. The quality and consistency of this data are crucial for creating precise digital models. Managing and analyzing these large amounts of data requires advanced data management systems and technologies, which is a complex and costly task for many companies.

Secondly, security aspects are of central importance. The networking of machines and systems with digital twins, i.e., the convergence of OT and IT, increases the complexity to be managed and potentially also the risk of security vulnerabilities. Companies must therefore implement robust security measures to protect their systems and digital twins, which requires additional investment and expertise. Finally, the technical complexity and the necessity to adapt or reconfigure existing systems can make the introduction of digital twins more difficult.

The lack of skilled personnel and experience in dealing with these technologies also proves to be a challenge.

On the technical side, open interfaces and protocols are needed to enable cross-organizational data exchange. To me, the technical implementation seems significantly easier than generating corresponding acceptance and openness in the executive offices. Is this impression deceptive?

Christian Heinrich: Even though it may seem simple at first glance, there are often significant technical hurdles. This can include the integration of legacy systems, adaptation to different technical standards, or ensuring data quality and consistency. Technical implementation often requires extensive testing and adjustments.

However, executives must also recognize the long-term benefits of standardization and be willing to invest in this direction. This may mean that existing business models and processes need to be reconsidered or even fundamentally changed.

In any case, the concept of business ecosystems, i.e., collaboration across company boundaries, seems to be moving forward. Almost daily, we currently read about new partnerships, which, however, still often develop between large tech companies. In your observation, how is it in medium-sized and small enterprises?

Christian Heinrich: SMEs benefit from collaborations with other companies, technology providers, and regional networks by gaining access to advanced technologies and expertise that they might not afford on their own. These partnerships enable them to use digital tools such as digital twins and IoT solutions efficiently without having to bear the high costs of in-house development.

Nevertheless, SMEs are often faced with obstacles such as limited financial resources and lack of expertise. Digital platforms and industry-specific initiatives provide support by acting as intermediaries and offering networks that make it easier for SMEs to integrate into larger business ecosystems. Implementation organizations like the Open Industry 4.0 Alliance help drive digital transformation and strengthen their competitiveness.

Politics, business, and research aim to support data-based collaboration through data spaces and corresponding initiatives like Manufacturing-X and concrete projects like Factory-X. How do you assess the progress here?

Ekrem Yigitdöl: We as the Open Industry 4.0 Alliance, or OI4 for short, are actively working on the Factory-X and Manufacturing-X projects. In Factory-X, 11 and in Manufacturing-X significantly more practical use cases are currently being implemented, where new concepts for using the Asset Administration Shell are also being developed.

Significant progress has already been made in the projects. However, it will take some time before these results are fully realized. Additionally, it is our shared responsibility to disseminate these advances, insights, and concepts beyond the circle of currently involved companies and make them accessible to a broader audience.

Therefore, OI4 is continuously working on internationalization to make the organization the leading entity in the field of Industry 4.0. The focus is initially on Europe, although we already have members from Asia and the Americas. We have already had a successful launch in the Netherlands, and now Denmark, Belgium, and Italy are next. We are deliberately looking for partners who know the local structures or conduct research and have market access. We talk to these organizations about showcases and participate in trade fairs. The most pressing issues for industry and economy can only be addressed together, internationally, and collaboratively. This is the only way to ensure that these innovative approaches resonate widely in the industry and are successfully applied in the long term.

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