Startup helps NXP, ST apply AI to semiconductor production

Startup helps NXP, ST apply AI to semiconductor production

Technology News |
By Peter Clarke

The company was founded by David Meyer, CEO, and Guglielmo Montone, CTO, and is using advanced AI techniques to use early and sparse data from process monitors to improve yield and minimize chipmaking equipment downtime.

The company’s business model is to provide a software product for fab-owners to operate and benefit from, Meyer said. So far the company has applied deep and transfer learning to etch, CVD and CMP processes, but the objective is to build an end-to-end yield predictor, he added.

Meyer said the approach appeals to chip manufacturers because Lynceus is able to model the relationship between process parameters and test results without requiring any changes in the production line or in testing protocols.

Guglielmo Montone, CTO, and David Meyer, CEO, of Lynceus. Source: Lynceus.

“Our initial results are positive – we predicted critical dimensions in a plasma etching process to within a 1nm accuracy – and we are now running a full set of experiments to benchmark the scalability, robustness and accuracy of our solution versus a broad range of existing modelling techniques, such as neural networks with fine tuning, neural networks alone, SVM [support vector machine], Random Forest,” said Meyer.

Meyer’s partner, Montone, has ten year’s research behind him specializing in Transfer Learning and invented an AI architecture used by Google DeepMind for autonomous driving. Transfer Learning is an approach to storing knowledge gained while solving one problem and applying to a different but related problem and can be key to working with efficiently with sparse data.

This means that working with sparse inputs, which might come from a processing machine and from the broader environment, the software can indicate what process tweaks may be needed to keep the machine operating in specification. This can reduce both downtime and the time taken when a machine is down. And with the tremendous value inherent in the work-in-progress, direct improvements here are highly valued by fab owners.

Next: Heading towards 28nm

“We’ve mainly been applying our approach to 90nm to 150nm processing nodes but 45nm and 28nm are in discussion,” Meyer said.

When asked how Lynceus had managed to get engagement with such high-profile customers so quickly, Meyer said: “We contacted people via Linkedin and I guess artificial intelligence is a hot topic. And we are at the forefront of AI. We also offer the first analysis for free working with a customer’s historical data.”

Lynceus can predict the results of quality tests from machine and process data. This means customers can see the potential benefit of Lynceus’ approach at no cost.

The work with Analog, NXP and ST is currently pre-deployment, Meyer said, but at the Avezzano wafer fab of Lfoundry in Italy deployment has already occurred. The software is in use to identify defects and monitor the performance of the etching process.

So far Lynceus has been sustained by €90,000 pre-seed funding from the Entrepreneur First incubator scheme and a couple of French government grants worth €120,000. The company is now working on a seed-funding round of €1.2 million, Meyer said.

The combination of deep and transfer learning AI is itself transferable with pharmaceutical production and PCB production in Lynceus’s sights. However, the high value of semiconductor production makes it a good place to start and focus, Meyer said.

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