A car is used as an example. All cars of a type have been produced using the same drawings and production instructions, and have the same average maintenance cycles. We call the models, simulations, and data from which all these cars are produced »master«.
2. Digital shadow
The digital shadow, on the other hand, represents the actual. It consists of data that is collected over the life cycle of the system depicted. This can be operating, status or process data that is recorded by sensors, for example.
The data shows the differences between each car, even though they are identical in construction. This is due to the fact that each car has been subjected to special features during production, such as assembly variations. During operation, the car may have been used in particularly hot, cold or dry regions, requiring shorter maintenance cycles. We call this data, which represents the reality of the unique car, »shadows«.
3. Intelligent linking
The real value of the digital twin comes from intelligently linking the digital master and the digital shadow.
By comparing the vehicle's master and shadow data, it is possible, for example, to predict the optimum time for maintenance or to derive important improvement potential for future product generations (feedback to design).