Lynceus Argo

The industry’s first AI-powered, model-driven platform that delivers accurate real-time predictions for the results of any manufacturing process step for every wafer manufactured.

Engineers don’t need to wait for the results of physical metrology to know that the key performance indicators (KPIs) of the current process step were met.

And if there is an excursion, engineers can react immediately with context-driven drill downs that enable them to identify the root cause and take any necessary actions.

Argo

A cloud-native software platform that supports multiple machine-learning predictive models to deliver Virtual Metrology for all the process steps in your fab.

  • Process-centric modeling approach
  • Combines domain expertise with AI/ML
  • Deployable on-prem or in the cloud
  • Real-time predictions for every process step

Easily deployable into any existing fab environment

Argo does not require a large, expensive big-data architecture. It only needs the data you already have from your MES system. Argo and its ML models run inline and in real-time in your fab delivering predictions for the results of every unit produced, and provides diagnostic visualization for all key metrics to aid in rapid root-cause-analysis of drift or excursion events.

Robust, production-proven results

For a mid-sized fab running 30,000 wafer starts per month, the ROI for one process step can equal $500K USD

  • ~$200K USD – The annual sampling reduction savings from physical metrology
  • ~$200K USD – The reduced scrap and material consumption due to faster excursion detection
  • ~$100K USD – The engineering time savings due to faster root-cause-diagnosis