Hermann Hänle
3. August 2018 0

Allow me to introduce you to… your twin

Twins are a godsend for research. People with the same genetic makeup are ideal for a range of biological experiments. Naturally, digitalization is not stopping at twins and has given birth to “digital twins.”

If the idea of digital twins reminds you of Arnold Schwarzenegger, you’re not actually that far off the mark. In “The 6th Day,” Schwarzenegger meets his clone and teams up with him to save the world (or his life). An extra on-demand ersatz Superman definitely has its advantages – including in manufacturing …

It all began with crash tests

The concept of the digital twin is being massively hyped at the moment in the manufacturing industry. And with good reason. Anyone who has witnessed a crash test before asks the question: why destroy a brand new car? In fact, the costs of the physical components that are destroyed in the tests are not insubstantial. It definitely makes sense to send an indestructible digital model onto the ramp and crush it instead of a Porsche, S-class Mercedes, Bentley, or Lamborghini. These simulations are a fixed part of the PLM process today and require detailed design data, calculation models, and considerable computing capacities.

Digital twin – the next step

The concept of the digital twin is going one step further, however: digital models for cars are not only being used for simulations in the design/development phase; rather, the entire car lifecycle is being represented digitally. Cars not only drive on the road, but around virtual worlds too. The computing model is aligned with real-world data and optimized.

The digital twin then becomes the key element between engineering, long-term car usage, and production. Experts talk of “closed loop lifecycle management.” Theoretical data from the factory and engineering office is continually optimized using practical experience from the real world. Sensors on board of real cars collect data while the car is running. This data is added to the computer model. Engineers can then make specific predictions, but also draw conclusions about the dimensioning of current components in the latest series.

Does the axle fit?

An example: as a rule, cars on the road have axles, which of course were also developed on car engineers’ digital drawing boards. When designing the axles, the engineers worked on the basis of specific framework conditions that they had established from their experience. Using the digital twin, the axle’s dimensioning can now be tested in detail. Sensors tell the digital twin what forces act in a dip, on a bend, or when braking. This shows the instances where the axle requires optimization.

And so the digital twin is assisting the birth of the next generation of cars, with new insights into the live responses of a car – a treasure trove for car designers. Digitalization makes it possible 😉

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