AI-based design and test automation

The development process for integrated sensor systems is very complex. Specialists such as analogue and digital circuit designers, verification and test engineers, software developers and others work closely together there. Design errors must be avoided as much as possible, as iterations and redesigns involve significant additional costs and time delays.

We are exploring the use of artificial intelligence to make the development process of integrated sensor systems safer and more cost-effective.

AI can support developers at many points in the process to avoid errors and apply informal knowledge that is difficult to map procedurally in an automated way. To achieve this, we are working on machine learning approaches whose algorithms learn, for example, the good design practices of experienced developers and provide valuable advice to even less experienced colleagues. In this way, review processes that are common practice in the design of integrated systems can be made more effective or even replaced.

AI also helps us to create fast simulation models. For example, we use neural networks to integrate non-functional properties into existing behavioural models very effectively. This in turn results in increased design reliability.

Artificial intelligence is also the key to evaluating large amounts of data, as is often the case when testing integrated circuits. Here we are working with AI as well to significantly relieve increasingly scarce personnel resources.