One-dimensional optimization takes companies further, but not necessarily to the goal they want to reach
Changed economic and political conditions, new business models and increased stakeholder demands for sustainable growth: The topic of “business transformation” is at the top of the agenda for many companies. In the viewpoint interview, Dr. Stephan Melzer, executive vice president industry and Dr. Wolfgang Bock, head of department industry 4.0 transformation & sustainability explain why and how “digital twins” can drive the digital transformation of companies.
For many companies, the terms “digitalization” and “business transformation” seem almost synonymous. Isn’t that a little short of the mark?
Stephan Melzer: Digitalization is not “low-hanging fruit”. Without striving for clarity and rigor, it simply remains a topic, nothing more. And those that only see the technical dimension, won’t get far with their transformation. One-dimensional optimization takes companies further, but not necessarily to the goal they want to reach. That’s why it is that we consciously look at what is supposed to be a technical topic from the perspective of the factors organization and people. Digitalization, which for me is always the balance of people, organization, technology and business purposes, is an important part of the business transformation. But, in my view, anyone who focuses on just one dimension is making a mistake. It is the greatest risk for bad investments.
Wolfgang Bock: Breaking new ground requires courage. It is an effort and a financial risk for everyone. Companies know that they have to change to remain competitive. This is not just about reducing unit costs, transparency, streamlining and diversifying supply chains but increasingly also about sustainable aspects such as reducing CO₂ and curbing resource consumption. Only those who look at the entire added value chain and analyze it in depth can reach good decisions. In practice, many companies feel not yet ready for the far-reaching and profound decisions that would be necessary for a successful business transformation. The issue here is that this decision node cannot untangle itself by magic.
How can this node be untangled? Can the use of “digital twins” drive transformation?
Wolfgang Bock: A manufacturing plant or production line cannot be renewed or completely replaced overnight. So, where to start? Digital twins digitally map the processes in a manufacturing plant or production line 1:1 using sensor technology. All physical data of the as-is state is collected in the digital shadow. Using a digital master, this data can be used to derive optimization measures and to set the pace for the target state. In the ideal case, digital twins already help to avoid errors during planning. This increases security, performance and overall prospects for success. Investments in the future become more transparent, measurable and plannable.
Stephan Melzer: Each company immediately becomes more strategically and operationally agile with the introduction of digital twins. We need to distinguish between the digitalization of the production and the digitalization of the product. Digitalized processes can increase efficiency in companies, while the digitalization of products creates totally new value and value propositions. In the ideal expansion stage, digital twins enable risk analyses, tests, simulations, evaluations of product development and even the development of new business models.
According to a study by msg and Fraunhofer IPK, 85 percent of the surveyed companies have already developed concepts for a digital twin. But implementation remains a challenge. Why is that?
Stephan Melzer: 35 percent of the companies with a concept for digital twins are in the process of implementing small projects. Only eight percent of the surveyed companies are tackling more extensive projects. That is far too little. When you see that such a central element as the digital twin has not yet found its way into general practice, then that worries me. Perhaps the topic is being conceived of too narrowly. Because it’s not just about the technical optimization of processes, but above all about creating more sustainable production. For me, digitalization is the key to curbing our resource depletion and optimizing emissions. These are pressing issues that should definitely be addressed now with full commitment.
Wolfgang Bock: One particularly pressing issue at present, supply chain bottlenecks, could lead to a rapid rethink among companies. This is because digital twins allow supply chain processes to be digitally recorded end-to-end, from raw materials to suppliers and sub-suppliers to distributors and transport routes. This way, supply bottlenecks can be identified early and transport costs can be optimized. At the same time, this this pays dividends for the sustainable growth of companies. Among other things, this would pave the way for energy and emission-optimized supply models, which reduce the carbon footprint of products.
Digital twins are already used in aviation, the automobile industry and communal areas. What about the other industries? Can you think of specific examples?
Wolfgang Bock: I’d like to give you two examples from different areas — from industrial plants and from the energy sector. The first example is a rolling mill, in which seamless steel pipes are rolled from a metal cylinder in several rolling units connected in series. Before entering a unit, the longitudinal profile of the pipe is measured. The data is transferred to the digital twin of the unit, which then calculates the frequencies of the rolling motors as a function of time based on historical data and AI methods in quasi-real time to compensate for unevenness and reduce the size of so-called double-sided trumpet ends that need to be cut off. This significantly improves the quality of the pipes but also reduces energy consumption because the cut off trumpet ends must be melted again.
Each rolled pipe is also represented by a digital twin, which, besides the serial number, the final longitudinal profile, the material and the energy consumption, also contains the CO₂ emission, the water consumption and various test certificates. The digital pipe twin is delivered with the physical pipe.
There are also exciting applications in the energy sector. At a district heating supplier, each of the house connection stations transmits sensor and heat meter data to a digital twin every three minutes. Based on historical data, the twin continuously checks whether there are any malfunctions or energetically unfavorable settings. If this is the case, the digital twin generates an alarm so that the malfunction can be promptly fixed. Suppliers can also use the historical data of digital twins to better forecast the necessary energy feed into the district heating network. After all, this is a highly topical issue in view of the high cost of fossil fuels and the reduction of CO₂ emissions.
In the projects described, digital twins are used in a company. If digital twins are used widely and across companies in the future, they must also be able to exchange information virtually — speak the same language, so to speak.
Wolfgang Bock: The digital twin generally enables cross-area and cross-process collaboration between different partners. Data ecosystems are essential so that the digital twin can also be used across companies. Catena-X and GAIA-X and interoperability standards such as the asset administration shell are important approaches here. Development has picked up pace — we only need to hope that international standards will also be established here. This way, even smaller companies can set-up a digital twin without having to operate the infrastructures themselves.
We have now talked about the near and somewhat more distant future. Which challenges should companies address now with high priority to accelerate their transformation?
Stephan Melzer: The challenge for companies is not the technology itself. The primary challenges are, besides the competence of employees, mainly also the access to and the quality of data that belongs to their own products. The data quality is high if data is complete, accurate, consistent, reliable and up-to-date. Companies in all industries should continuously deal with data of their own products and its quality. This is the only way they can remain competitive. Because whether for product optimization, process automation or simulation through a digital twin — the systematic collection and analysis of data will be essential in the future.
