Making digital twins more accurate

Creating a schematic representation of reality – a model – isn’t new. Modeling has been around for years: from tangible scale models of the solar system, buildings, or bridges, to mathematical models describing all kinds of real-world systems.

According to PhD candidate Bas Kessels, a good model has “infinite possibilities.” But that’s just the thing: when can you say a model is ‘good’?

“The mathematical models that are currently being made of real-world systems have physical, comprehensible laws as their basis. But we see that these laws aren’t fully capable of accurately describing all the behavior you observe in a real-world system.”

When can you say a model is ‘good’?

“And so you get a mismatch between model and real-world system. Not an ideal situation if you’re using that model to make predictions or decisions for your real-world system, for example.”

A good model is comprehensible and accurate. As the latter is often lacking still, Kessels took to his computer to develop new methods that would lead to more accurate digital twins, especially of complex systems. To do so, he used neural networks, Kessels explains.

“This is because you can train these neural networks based on data measured in the real-world system. And with that, the networks can compensate for the incorrect or not modeled dynamic behavior of the real-world system.” What’s unique about Kessels’ approach is that even dynamic, nonlinear systems can now be described more accurately.

Kessels then tested his new methodology at semiconductor company ASMPT in Beuningen, which wanted a more precise model of their wire bonder. This is a device used to connect chips to a circuit board, or any other electronic component. Each chip involves many gold wires that need to be connected, a lightning-fast process that takes place at the micrometer (or sub-micrometer) level.

“Such a wire bonder accurately attaches wires to a chip. However, this can’t be done immediately; when the device arrives at the right location, it vibrates for a short time. Precision bonding is only possible when the device is virtually stationary. With my model, we can now map the vibration much better, so the waiting time can be shorter. And that means more chips can be handled per minute.”