A Common Language for Machines: Industry 4.0 in Practice
Professor Dr.-Ing. Martin Ruskowski is Chairman of the Board at SmartFactory Kaiserslautern, heads the ‘Innovative Factory Systems’ research division at DFKI, and holds the Chair of ‘Machine Tools and Control Systems’ at RPTU. Having held positions at companies including KUKA and Lenze, he has been working since 2019 with around 40 companies and 80 researchers to develop the production of the future, integrating theory and practice under real-world conditions.
6 Nov 2026Share
Production systems are becoming increasingly complex, with more software, more interfaces and more manufacturers. What are the most common reasons for the failure of Industry 4.0 implementation in practice, and what do companies tend to underestimate in this regard?
Often, there is a lack of common architecture into which new technologies can be meaningfully integrated. Companies digitise individual machines or processes, but the link between production and IT remains patchy. Every additional application then requires its own interfaces and individual adaptations. As a result, complexity increases with every solution.
Above all, companies underestimate the preparatory work: What data do we need? What does it mean? How do we describe machine capabilities in such a way that different applications can utilise them? These questions must be answered jointly by production, automation and IT. Industry 4.0 is therefore also an organisational challenge. With our Open SmartFactory Architecture, we demonstrate how this collaboration can be built on a consistent technical foundation. It is crucial that companies can integrate new functions without having to overhaul the entire system with every expansion.
You bring together machines from different manufacturers within a shared facility. What becomes apparent when systems must work together, and where do the biggest hurdles lie in terms of interoperability and standards?
In such a shared facility, it quickly becomes clear that a functioning data connection is by no means sufficient to ensure that two systems understand one another. They must also share the same understanding of what a piece of information means, what capabilities a machine offers, and under what conditions these can be executed.
The biggest hurdles often lie in differing data models, room for interpretation and manufacturer-specific extensions. Even if both sides use the same standard, interoperability is therefore not automatically guaranteed. Standards must be implemented precisely and tested together in a live environment. This is precisely why our model factory is so important: it is here that solutions from different manufacturers come together under real-world conditions. With OpenSMI, we make machine capabilities accessible via uniformly described skills. Higher-level applications can utilise these without needing to know the internal technical implementation of each machine.
Which specific solution or demonstrator will SmartFactory-KL be showcasing at HM27, and what can visitors experience live there that a concept paper cannot show?
At the 2027 Hannover Messe, we will use our model factory to demonstrate how machines, AI agents and autonomous robots come together to form a flexible production system. Our Open SmartFactory Architecture forms the basis for this. OpenSMI makes the capabilities of the machines accessible via a common interface; AI agents can then coordinate production tasks based on this.
Visitors experience the interplay between machining and material handling: a workpiece must be transported to the appropriate station, machined there and then transported onwards. For this to happen, software decisions, machine statuses and physical processes must all align. This is precisely what a concept paper can only convey to a limited extent. The ongoing demonstrator shows exactly what information and feedback are required for this. We use this to demonstrate how existing machine capabilities can be combined to form different processes and what conditions are required for adaptable production.
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