Presentation
STAMP: Semiconductor Tool-Chain Attestation Through Wafer-Level Machine Learning-Based Process Monitoring
DescriptionWe introduce a machine learning approach for distinguishing between wafers fabricated using a sanctioned/ratified chain of tools on a semiconductor manufacturing floor and unsanctioned/unratified versions of the tool-chain based on metrology or wafer acceptance test collected during manufacturing and testing. Our method exploits the systematic nature of process variation and captures the subtle causal relationships between tool exchanges and the resulting changes in physical dimensions or electrical characteristics of the silicon, which can then be used for enabling wafer-level tool-chain attestation. Effectiveness of our solution is demonstrated on a dataset of inline and e-test measurements from 7000 wafers fabricated with multiple tool-chain variants in the GlobalFoundries 12LP FinFET technology node.
Event Type
Research Manuscript
TimeTuesday, July 2812:16pm - 12:30pm PDT
LocationMtg Room 203C