Text Ulrich Kläsener, Hans-Robert Koch ––– Photography
Three digital twins and the smart factory in times of volatile global markets – Markus Asch, CEO of Rittal International and Rittal Software Systems, and Prof. Oliver Riedel, Director of the Fraunhofer Institute for Industrial Engineering IAO and Managing Director of the University of Stuttgart’s Institute for Control Engineering, outline and evaluate the current situation, pinpoint challenges and identify the opportunities of the digital transformation of the manufacturing industry through the networking of ecosystems.
Industry 4.0 has dominated discussions in industrial circles for ten years now. Is it mission accomplished?
Prof. Oliver Riedel: Let me use a cooking analogy with regard to industry 4.0 and the smart factory. The recipe is there, the ingredients are freely available and there are even a number of chefs who can make the dish.
That sounds encouraging.
Riedel: There’s just one problem – the vast majority of factories are brownfield sites that have been in existence for years, or even decades, and have long-established structures. These are not yet fully depreciated. Take the example of a paintshop with a 30-year depreciation period. If you drop in to see the owner and request a completely new design concept, you will immediately be sent packing by the financial controller, if not sooner.
What’s the answer, Prof. Riedel?
Riedel: With regard to a brownfield site, only a gradual approach will work. I recommend step-by-step implementation, with a corresponding evaluation of the economic benefits. This issue doesn’t arise in greenfield projects, where it should be Industry 4.0 all the way.
Are you aware of any flagship projects that are already in line with Industry 4.0 criteria?
Riedel: There are certainly some distinct manufacturing processes where it already works today: with simple structures, with low product variation, production on modern equipment and consideration of data consistency.
A serious market player recently made a bold statement that we’re 80 per cent of the way towards the fully fledged smart factory. Do you share this assessment, Mr. Asch?
Markus Asch: No, that isn’t the case. We’re a long way from being in a situation where the factory optimises itself. However, I believe we’ve tapped into nearly a third of its full potential.
What do we have and what don’t we as yet?
Asch: The first step was to create smart components. These are now available. The next step was to create uniform data standards. These, too, are now largely in place. What we don’t have yet is compatible content at critical data points. If you compare the error messages of 20 automation systems, it’s an absolute jungle.
What do you conclude from that?
Asch: What we need to do now is create transparency regarding digital twins and understand how these are interlinked. In the most advanced factories, we are currently in a position to use transparency to find out exactly what we can optimise. We can gain new insights first and foremost by matching the data from the digital twins.
Which digital twins are you referring to?
Asch: As we see it, three digital twins need to be connected in a seamless and meaningful way to achieve smart production. In the manufacturing context, you see, there are three ecosystems that should ideally generate a digital twin - systems, products and manufacturing processes. The more effectively companies are able to usefully connect and link the data from these three digital twins in the manufacturing process, the faster their progress towards the smart factory will be.
What do you consider to be the major hurdles during the digital transformation?
Riedel: Proprietary systems are toxic – non-open standards are the biggest obstacle. In other words, it’s all about the end-to-end availability of data, and this digital continuity must be based on open standards at all levels. If we look at how machines currently communicate with each other and how data is shared, this is often primarily used to compartmentalise ecosystems rather than to open them up.
Asch: Digital continuity is one thing, but data also needs to be contextualised – all the more since digital twins from all kinds of areas contribute to production. If you feed production data into an AI engine at the moment, you’ll get nothing out, nothing at all. You might as well save yourself the bother. You can’t do anything without domain knowledge, without assigning data to a logical ecosystem. Our plant in Haiger generates 18 terabytes of data every day. The big challenge is knowing which two terabytes are actually important in which process.
You are assuming we will see far greater progress towards the smart factory over the next five years than we did in the previous ten. Why is that?
Asch: For one thing, besides the data itself, we now have the relevant understanding of the digital twins, the data points and the ecosystems. For another, change will put us under unimaginable pressure. We are gradually heading for a perfect storm. Without digital continuity in our production operations, we won’t have any hope of successfully meeting the various challenges.
Can you make the idea of a perfect storm a little less daunting by explaining what exactly we are talking about?
Asch: Urgent necessities such as energy efficiency. Not one single production operation is being managed on this basis at present, because gas and electricity have always previously been available and affordable. In terms of flexibility - and in response to scarce resources, component shortages, even more frequent factory reorganisations and volatile order behaviour – we also need to take another look at processes that have become ingrained over decades. All this pushes companies relying on conventional approaches to their limits.
Why are businesses that operate a smart factory in a better position than more traditional or conventional companies to cope with this new market volatility when it comes to things like energy?
Riedel: Knowing not just how much energy my process consumes in total, but also exact details about where and when, means I can shift production to periods when energy is cheaper and more available, for instance. That marks a transition from open-loop to closed-loop control, because the parameters involved in production are, as a whole, becoming high dimensional. Companies very quickly need to introduce smart management of things such as energy, skilled personnel and materials. All that currently costs an awful lot of money. Incidentally, data-assisted prior simulation and the playing out of processes with profiles that can be modified as required in the digital ecosystem provide a very effective decision-making tool for the management team. Conventional or standard regular statistics are no longer adequate.
The apparent urgency is rather like the debate surrounding the guiding principle of “resilience through adaptability”, isn’t it?
Asch: What does resilience actually mean? It means starting by understanding the world in which we are living. If we do that, if we accept the reality and draw the right conclusions, the perfect storm is also the perfect basis for solutions. You need the ability to understand how things are interlinked and to adapt accordingly.
Which industry sector is most likely to make the quickest progress?
Asch: The production industry – from SMEs to large corporations. It uses huge amounts of energy.
What is the best approach right now?
Asch: Essentially, looking for the right partners and making a start on automating production, because that’s where the efficiency gains are greatest. The next steps are to create data spaces and to learn.
You recommend learning fast.
Asch: In general terms, we recommend not starting any initiatives with megaprojects that will take two years to produce initial findings. You need to restructure anything that won’t produce findings within the next six months. It’s what you learn from implementation, not the concept, that matters. Instead of having people spend months considering which data might be relevant, let them learn instead by actually working with the data.
How do you get people on board with the digital transformation?
Riedel: Complexity isn’t necessarily a bad thing, but don’t make life complicated. The important thing is that everyone involved, from ordinary workers to shift supervisors, needs tools that are really easy to access.
Asch: That’s exactly how we see it, too. People – especially those with process experience and expertise – should be given the right tools, preferably also based on no-code or low-code approaches.
Riedel: Make it very simple for workers to access a database via an interface, without having to log in or use complicated language – that enables them to spontanously ask questions such as how many quality problems have there been with a particular product over the past fortnight, broken down according to shifts and systems. I’m certain they will ask questions - the right questions - and so much quicker. You can use incentives or concessions to give the whole thing a push, as has previously been done with CIP.
All that remains is to gaze into the crystal ball – when will the smart factory be an industry-wide reality
Riedel: When production data can reveal the cause of problems, whether that’s production planning errors, overlooked details or gaps in product development. I can guarantee that the issue as a whole will be occupying us for the next 10 to 15 years. It may take another ten years to achieve full virtual commissioning, and twelve for the digital factory – in other words, digital process planning and design – to become a reality. The digitalization of manufacturing depends to a great extent on investment behaviour. What takes the most time is getting product data back from the field and into the product development department.
Thank you very much for the interview!