Diagnosing timing related cell internal defects for FinFET technology

Abstract

The semiconductor industry is encountering an increasing number of front-end-of-line defects in the advanced FinFET technology nodes due to extremely small feature size and complex manufacturing processes required for FinFET transistors. Traditional delay diagnosis algorithm has a limited support for cell internal timing related failures based on transition delay faults, and tends to provide a large suspect list. It cannot provide the precise defect location inside the cell that is necessary for effective physical failure analysis and statistical yield learning. In this work, we present a new cell-aware delay diagnosis algorithm, based on accurate delay fault models derived by analog simulation, which can pinpoint the defect location within a cell for various timing related cell internal defects. Preliminary results for real silicon failures show that significant diagnosis resolution improvement can be achieved by the proposed method.