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Professor Resch, how do you imagine a digital twin?
The term means creating a twin of something real in the digital world. Things can also be tried out virtually on it that would be very complex on a real object.
For whom does a digital twin offer advantages?
This is the case, for example, in the automotive industry or the aerospace industry. Among other things, it is about the manufacturability and plannability of products. To investigate this, you first build a car or an airplane on the computer – with all the important parts and functions. Thanks to advances in computing power, we are now able to represent almost anything digitally – and test whether it works. This can also be done with a building, a piece of clothing or an entire community. Its digital image can be used, among other things, to examine traffic flows after the construction of a new road or bridge and their consequences.
How complex is it to create a digital twin?
Creating a digital twin from scratch – i.e. when no data is available – is very time-consuming. However, digital instruments are already being used in most areas – for example in industry, where designers have been working with CAD technology for a long time. Products or components are designed on the computer and the resulting electronic description can be integrated into a digital twin. In municipal planning, there are geographic information systems that contain data on the risk of flooding or the age structure of the population in individual parts of the city. They can also serve as the basis for a digital twin. However, care must be taken to ensure that appropriate and up-to-date data is used – and that you combine it correctly to get an overall view of a product or community.
To what extent do high-performance computers play a role in this?
The central theme is digital convergence. For about 15 years people have been talking about big data and the end of theory. The idea is: We have so much data that we no longer need to understand what’s behind it. However, this presupposes that clever questions are asked of the huge amounts of data. This is the only way to gain new insights. What’s behind the data? And how are these related? And in order to be able to ask smart questions, methods are required to analyze the data. This includes, for example, artificial intelligence. Finally, the last point is: In order to analyze the abundance of data, enormous computing power is required. So three things have to come together: a lot of data, an analysis method like artificial intelligence and a high-performance computer. Only with this combination can complex relationships be recognized using a digital twin.