Fabtex™ Yield Optimizer is a cutting-edge software platform designed to help semiconductor foundries accelerate yield ramp and improve high-volume manufacturing performance. By leveraging virtual silicon twins—created in SEMulator3D® and validated against real fab data — Fabtex combines physics-based modeling with machine learning to diagnose and resolve process-limited yield issues.
Engineers can simulate entire process flows, apply virtual process variations, and perform Pareto analysis using virtual metrology to pinpoint high-impact process parameters. This can enable faster identification of failure modes, improved yield, and reduced time to market.
Fabtex™ Yield Optimizer is the only platform that combines validated virtual twins, physics-based process modeling, and machine learning to deliver comprehensive yield insights. Whether you’re ramping a new technology or optimizing mature nodes, Fabtex empowers engineers to make smarter, faster decisions.
Modern semiconductor technologies are increasingly complex, with 3D structures and tight process integration requirements. Traditional yield improvement methods—focused on isolated issues and wafer-based testing—are slow, costly, and often counterproductive.
Fabtex™ Yield Optimizer addresses these challenges by:
Unlike standalone machine learning approaches, Fabtex delivers causality, backtracking, and root-cause analysis by integrating physics-based simulations with AI.