Another logical step is the use of generative AI in engineering. There, AI can suggest program code in natural language, automatically create documentation, or support visualizations. This makes engineering even more efficient and user-friendly. Again, the openness of our platform is advantageous, as such functions can be seamlessly integrated – whether via established developer tools or specialized partner solutions.

What concrete advantages does AI offer for optimizing manufacturing processes for your customers?

Even today, our customers particularly benefit in the engineering process from the possibilities of Artificial Intelligence. It supports information gathering, decision-making, and configuration, facilitates application engineering, and accelerates software development. As a result, development cycles can be significantly shortened and efficiency in project execution noticeably increased. In some more conservative industries, we still see a somewhat more cautious application so far, but the potential is clearly visible there as well. Step by step, AI is thus becoming an important driver for the optimization of manufacturing processes – not only in development, but in the future also in production, service, and quality assurance.

How does AI change your automation solutions with regard to predictive maintenance?

Predictive maintenance is not a new topic for us but has been a fixed part of our automation solutions for many years. Even today, we offer systems such as the Product Health Index or predictive analysis tools that can detect and interpret anomalies in connected mechanics – and this already works impressively reliably without the use of AI. However, Artificial Intelligence gives us the opportunity to further refine these analyses and significantly increase their reliability. Particularly important here is that we receive data from the field over the entire life cycle. Only in this way can models be continuously trained and the quality of predictions improved. AI thus becomes an important lever to make predictive maintenance even more precise, efficient, and easier for the user to apply.

Are there pilot projects in which AI is making your motion-control systems smarter?

A particularly illustrative example comes from an application at Kohlbacher GmbH. There, the classic task of the “saw doctor” – the precise reworking and sharpening of band saw blades – was automated with the help of Artificial Intelligence. In the fully automated straightening center Hammerhead 3000, a solution based on ctrlX Automation takes on this task. The combination of ctrlX Core, ctrlX Motion, ctrlX Drive, and an AI app enables direct access to control data via the ctrlX Data Layer. During the sharpening process, the system continuously learns and independently optimizes the straightening times. The result is increased precision, higher efficiency, and sustainable resource utilization. This clearly shows how AI makes motion-control systems smarter, more economical, and more user-friendly.

How do you integrate AI into your customers’ existing machine parks?

We pursue the same approach here as already described: an open toolbox, a flexible platform, continuous data integration, and scalability. Especially in brownfield environments, the provision of data plays a central role, as older machines are often not networked. With our solutions, this data can be accessed and connected to higher-level AI-supported systems. In this way, existing plants also become smarter step by step.

A crucial factor in networking machine parks, particularly in brownfield environments, is ensuring the highest level of IT security. That is why we place the greatest importance on robust and secure data communication. Our industrial operating system ctrlX OS is certified according to IEC 62443 Security Level 2 and thus enables our customers to protect their valuable machine data and operations against cyber threats.

Which data is particularly relevant for your AI solutions?

For us, the principle of data sovereignty comes first: our customers’ application data belongs to the customers, and we only use it when cooperation is based on mutual agreement. In such projects, genuine added value is created on both sides, because together we can develop solutions that become increasingly precise through the targeted use of data. In addition, the usage data of our own products is naturally of great importance to us. They provide us with insights into behavior in the field and allow us to continuously develop and optimize our systems. Some customers actively share this data with us or grant us access, so that we can gradually improve products and services. In this way, relevant data not only contributes to increasing efficiency but also ensures the continuous further development of our automation solutions.

With which partners or networks are you driving the topic forward?

As part of ctrlX World, we cooperate with partners who contribute their specific solutions to our open platform. This includes, for example, 36ZERO Vision GmbH, which provides AI-supported software for visual quality assurance and thus enables automated defect detection in production processes. The company logiccloud is also part of the network: it offers cloud-based engineering and PLC programming, supported by AI functions that simplify and accelerate software development. The portfolio is complemented by Landing AI, a partner providing AI-based solutions for industrial image recognition that make quality inspections more flexible and efficient. In this way, we are strategically expanding our ecosystem with practical AI applications that our customers can directly use in their development and production environments.

How do you ensure that your customers quickly achieve ROI on their AI investments?

Whether and how quickly AI investments pay off always depends on the specific use case. Our task is to provide the technical prerequisites with an open platform and scalable tools. The specific ROI is defined and assessed by the customer themselves – depending on goals, processes, and economic conditions.

Do you see regulatory hurdles for Industrial AI?

Regulatory hurdles exist and will continue to grow in importance in the future. We are already addressing them today through the secure and certifiable architecture of our operating system ctrlX OS and the ctrlX Core controller, which are based on the principles of “secure by design” and enable regular updates – fully in line with the Cyber Resilience Act. In addition, the requirements of the EU AI Act must be taken into account, for example with regard to conformity assessment and transparency of AI systems. We naturally comply with these growing regulations but at the same time see it as our task to ensure that companies are not slowed down too much by them. Our ambition is to guarantee security and reliability while leaving enough room for innovation and practical progress.

Where will Bosch Rexroth stand on the topic of AI in five years?

Given the dynamics of recent years, a linear forecast would hardly be serious. The development of AI is advancing so rapidly that we can certainly expect further disruptive changes in the next five years. Topics such as agent systems, which independently coordinate tasks and prepare decisions, or Physical AI, i.e., the direct use of AI in physical automation systems, will play an increasingly important role. For us, this means we must remain open-minded, actively seize opportunities, and at the same time shape the framework conditions so that our customers can always use safe, reliable, and practical solutions. But it is also crucial to keep the discussion factual: we must not idealize AI too much, but want to transfer its potential specifically and responsibly into industrial applications.