Mr. Meuser, the path to a data-driven business model in manufacturing is often described as a "path over rocky new territory" - where do you see the biggest 'stones' on this path?

Dieter Meuser: Above all, no compromises can be made when it comes to data quality. But that's much easier said than done! First of all, all machines have to be networked - but we don't usually have consistent standards yet; even with relatively new machines with an interface for OPC UA, the versions often still differ. The next step determines the usability of the mass of data: users have to put the data into context in order to understand it. This requires a great deal of domain knowledge about automation and manufacturing processes.

In a factory like the Rittal RKS plant in Haiger, for example, over 300,000 data points quickly accumulate, which must be correlated with the master and transaction data of the factory's PLM and ERP system. This means recognizing which sensor measures which data on which machine and what conclusions can be drawn from this about the production process. The good news is that anyone who has managed to do this can quickly benefit from the data, for example through a complete virtual overview of all processes in near real time. On this basis, the production specialists can find errors and optimize the processes. We have implemented this at the Rittal plant in Haiger, for example.

This results in 'homework' for manufacturing companies to realize their own smart factory.

The onus is not only on the manufacturing companies, but also on their partners in the industrial environment. Together, they must use their manufacturing experience to connect the world of automation with that of IIoT and IT. And they need to do this at the data level of the various ecosystems as well as at the human level. Partners such as the industrial division of German Edge Cloud, with its roots in both industrial domains, are not the only ones who can help. Machine, control and switchgear manufacturers can also contribute to a faster start to networking.

For example, the software from our sister company Eplan is the standard for engineering the electrical components of machines and ensures high data quality in control and switchgear engineering implemented with Rittal Systemtechnik. Ideally, the factory operator receives a digital twin of the machines on his store floor with complete information on all the electrical components of his systems. This data then helps GEC with its 'Oncite Digital Production System' to increase the speed of networking and data contextualization.

What does the future of the German manufacturing industry look like in terms of the smart factory?

Basically, it is important to bring the digital transformation to the masses quickly, especially among medium-sized suppliers as the backbone for the automotive industry's digital supply chains. This is what drives us as a founding member and advisory board member of the open automotive data ecosystem Catena-X.

Within the factory, many companies are now facing the next phase towards 'smart': the transition from the rather rigid 'execution' of their processes to more agility and IIoT-supported control functions - i.e. manufacturing operations management in near real time. To achieve this, store floor-related master and transaction data must be validly supplemented with sensor data. One obstacle is often the lack of flexibility of many existing MES/PCS/Scada applications due to their monolithic software architecture. Software that uses the Industrial IoT with modern microservices leads to the goal faster and more cost-effectively.

How can GEC support companies in this process?

Dieter Meuser is CEO Digital Industrial Solutions at German Edge Cloud

© German Edge Cloud

To ensure agile production management, manufacturing companies need to link industrial IoT applications with existing IT systems such as PLM, ERP, MES and Scada. To support this, we have supplemented our cloud-native IIoT applications with 'Best of Breed' partner products in the 'Oncite Industrial Suite' and built them into the overall 'Oncite Digital Production System (DPS)' system, with the 'Oncite Factory Edge' on board as an infrastructure option.

With microservices, we enable the entire spectrum; from the networking of systems to the visualization of processes or applications such as Track&Trace through to comprehensive production management. The most common case is the gradual modernization of brownfield production, especially in medium-sized companies. It is therefore important for companies that IIoT applications with microservices can also be used in parallel with existing IT/OT infrastructures and operated in different environments. This may be followed later by the gradual migration of existing monolithic MES/PCS/Scada systems to more modern digital production platforms such as the 'Oncite Industrial Suite' with the appropriate infrastructure of the highly scalable 'Oncite Factory Edges'.