In the context of predictive maintenance, a digital twin is a detailed digitalized model of a product and its behaviour under various loads during operation. This behavior is described by real and virtual, i.e. simulation-based sensors. Operators of systems or devices benefit from digital twins through improved product availability. Precise knowledge of the current system status and emerging problems, e.g. triggered by wear and tear, not only prevents downtimes and production losses, but also makes the work of operating personnel safer.

In addition, digital twins also allow a look into the future and show how operations can be systematically optimized, for example by balancing energy costs, running time, maintenance requirements, system performance and product quality.