According to research on twins, their genetic features are not the only reason they feel, think and act alike. External environmental influences are also a factor. Common experiences cause twins to develop in the same way. Scientific research into what it is to be a twin dates back almost 150 years. By comparison, research focusing on the virtual equivalent – the digital twin – is still in its infancy. Despite that, the digital twin has become synonymous with the industrial revolution and is feted as a key trailblazer accompanying Industry 4.0.
According to IDC FutureScape 2018, just two years from now, 30 per cent of the world’s 2,000 largest companies will be using data from digital twins to improve the success rate of product innovations and raise productivity. The market research company is forecasting productivity gains of up to 25 per cent. Gartner, another market research company, also sees digital twins as a positive development. It predicts that half of large industrial companies will already be working with these virtual avatars by 2021 and improving their productivity by up to ten per cent as a result.
New value creation
“The digital twin opens the door to new, exciting areas of business for industrial companies,” agrees Prof. Rainer Stark, Chair of Industrial Information Technology at the Technical University of Berlin and Director of the Virtual Product Creation division at the Fraunhofer Institute for Production Systems and Design Technology IPK, whose research in this field dates back ten years. “Value creation used to be confined to the real world, but the digital twin is now laying the foundation for companies to obtain information from the actual product life cycle for further processing. This gives models that have to date been restricted to the start of the development chain a new value creation component and they now accompany a product throughout its entire life cycle,” he explains.
In the automotive industry, for example, this could help create a more customised driving experience by offering additional functions that suit a particular driving style. Use-based findings could also be incorporated into the design of further models. In the production environment, there is potential for deviations from the norm to be detected and rectified faster because problems such as tool wear would be identified at an early stage. Ad hoc changes to production workflows would also be conceivable, with their effects being simulated prior to commissioning. According to industry association Bitkom, the economic potential of all digital twins in the production sector will total over 78 million euros by 2025.
An empathic nature
This is all down to the nature of the digital twin. “The way the digital twin is interpreted varies a great deal. According to our definition, it’s the digital depiction of a specific product, using models, information and data to define this product’s characteristics, status and behaviour. It’s based on a digital master – the original virtual model according to which the product is to be manufactured,” says Stark. In the digital master, developers define what the product will look like and how it will work. Attribute models are then added. These computation models provide information about what happens if the product starts vibrating, how it reacts to impacts or collisions, how it is opened and closed, and so on.
