The concept of the digital twin aims to mirror real products, objects, systems and processes at the digital level. For this purpose, the forces impacting upon components, such as temperature, pressure, tension, vibration and friction, are tracked, transmitted and processed in real time using sensors. By permanently comparing real components and digital copies, it is possible to realistically simulate reality. Machine learning makes it possible to precisely forecast component failure, while repair and maintenance intervals can be adapted according to need.
In addition, the collected data is used to detect production errors at an early stage and continuously optimize systems and machines.