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.

In addition to the pure hardware business, digital twins enable providers to offer completely new services – think of maintenance recommendations, spare parts management or mileage management. Such additional, operations-oriented services can be a valuable building block for establishing or consolidating long-term customer relationships, as they improve feedback on actual usage and the need for future product features.

The digital twin must adapt to the individual requirements of the end customer – in terms of the processes to be mapped and the IT infrastructure used.

A detailed concept for integrating the digital twin into the IT infrastructure is the most important building block for implementation. This includes defining the handling of sensor data, the real-time requirements of the system, the storage and visualization of the results as well as the security requirements of the system and compliance requirements.

Another question that needs to be answered at an early stage is the operating mode of the digital twin. In principle, the digital twin can be operated in an externally or internally managed cloud service, on systems in the company’s own data center or at the edge in the immediate vicinity of the physical asset. Each operating mode has its advantages and disadvantages depending on the customer’s use case and requirements.