Rittal and the Fraunhofer Institute in Germany explain the implementation of the digital twin

How to promote the further development of smart factories and smart production?

The Rittal Hager plant in Germany illustrates how the smart factory can be accelerated with a digital twin in manufacturing!

Rittal and the Fraunhofer Institute in Germany explain the implementation of the digital twin

　　As one of the world's most modern cabinet production sites, the Hager plant produces around 8,000 AX compact cabinets (click to download) and KX small cabinets (click to download) in a highly automated manner on a 24,000 square meter production site using more than 250 networked high-tech machines and plant components. The data analysis solution for the production line is based on the ONCITE digital production system, the core product of the edge cloud in Germany from Rittal Brothers. The integrated platform also includes the production of 3D models. The platform acts as a central data center, collecting vast amounts of data from a variety of sensors, coordinating the data and putting it into a loop of analytics, alerting, and real-time dashboards.

When it comes to digital twins, we hear from Markus Asch, CEO of Rittal International and Rittal Software Systems, and Oliver Riedel, University Professor and Dr. Doctor of Engineering at ·· Fraunhofer Institute for Industrial Engineering and Director of the Institute for Control Technology at the University of Stuttgart.

Q1. Recently, some market players have boldly claimed that the maturity of smart factories has reached 80%. Do you think so too?

Ashe: That's not the case. But I think we've reached the upper third of the factory intelligence pyramid.

The key now is to establish transparency and understand the interconnectedness of the digital twin. Most importantly, data matching from digital twins can generate new insights.

Q2: You mentioned digital twins. What does that mean?

Ashe: In our view, there should be three digital twins that are organically integrated with intelligent production. Ideally, the three ecosystems of the manufacturing industry should form a digital twin – equipment, products, and production processes. The faster a company moves on the road to a smart factory, the more it will be able to effectively connect the information from the three digital twins in the manufacturing process.

Q3. Compared with traditional factories, why are smart factory operators more able to cope with new energy fluctuations?

Riddle: If I know not only how much energy is consumed in the production process, but also when and where it is consumed, I can move production to periods when there is plenty of energy. This is no longer control, but regulation. The environmental parameters in production as a whole have become more hierarchical and multi-dimensional. Companies must quickly establish intelligent management of energy, professional talent, materials and other elements. The current cost of such factors of production is high. By the way: data-backed pre-simulations and process simulations that can change the configuration of the digital ecosystem at will are great tools for management decision-making. This is not possible with ordinary statistical methods.

Q4: How to lead everyone forward together in the process of digital transformation?

Riddle: Give workers easy access to the database, without having to log in or a complex programming language as a foundation, but through an interface where they can ask questions at any time: 'Dear database, how many quality issues have this or that product had in the last 14 days?' Please sort by shift and equipment. I believe that workers can ask questions of the system much faster than we can think for them. Overall progress can be driven through gamification and profit incentives, as in the previous continuous improvement process.

Q5. The future is still uncertain: when will the popularization of smart factories be realized across the industry?

Riddle: When production data can point to the cause and effect of problems: errors in production planning, overlooked details, loopholes in product creation. In the next 10 to 15 years, the whole industry will definitely be working on this topic. It may take another ten years to fully operate virtually. For a digital factory, it takes twelve years to plan and design digital processes. The digitalization of manufacturing is largely dependent on investment behavior. Product data takes the most time from the field to production.

　　Realizing a digital twin in completely different areas of industrial production requires three effectively connected digital twins – the twin of the device, the product, and the manufacturing process.

Rittal and the Fraunhofer Institute in Germany explain the implementation of the digital twin

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