Applying Artificial Intelligence in Fab Technology Co-Optimization (FTCO™)

The common approach to optimize a fabrication process involves process and fab engineers creating and setting up Design of Experiments (DoEs) using a trial-and-error approach. This approach often leads to costly iterations since wafer fabrication is both expensive and time-consuming. Typically, it can take weeks to months of experimentation, depending on what process parameters are not meeting their targets.

The new approach described in this webinar, already in production use today, leverages artificial intelligence (AI) and machine learning (ML) to generate an accurate model of a fabrication step. The approach involves using TCAD digital models of a fab process (digital twin) that consider the actual physics and chemistry involved. This digital twin model is used to test and analyze using the same DoE methodology, but without the need to fabricate multiple wafers, thus saving the cycle times and costs associated with the fabrication.

This webinar will showcase this FTCO flow with examples to give you more insight into this flow and how you can apply it for you and your team’s needs.

What You Will Learn

• Introduction to FTCO
  • Digital Twin
  • Machine learning
  • Fab Technology Co-Optimization (FTCO™)
  • Overview of Silvaco’s tools enabling FTCO
• FTCO for Process Margin Analysis
  • Use case example: STI trench modeling and optimization
• RTSM: A Real-Time 2D Structure Modeling Tool
• Other FTCO examples

Presenter

Dr. Christian Caillat is a Senior Staff CAE at Silvaco, based in Boise, ID. Prior to joining Silvaco in June 2023, he was with Micron Technology for 13 years, where he contributed to various projects including emerging memory program collaboration with imec, 3D NAND Cell team lead, and advanced memory modeling.

Dr. Caillat holds an engineering degree in Electronics and a PhD in Microelectronics from the National Polytechnical Institute of Grenoble (France).

WHO SHOULD ATTEND:

TCAD Engineers, fab engineers, process engineers, product managers, and engineering management.