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Optimizing Test to Enable Diagnosis-Driven Yield Analysis

Posted in: Silicon Learning

Using diagnosis-driven yield analysis, companies have decreased their time to yield, managed manufacturing excursions and recovered yield caused by systematic defects. Dramatic time savings and yield gains have been proven using these methods. Companies must plan ahead to advantage of diagnosis-driven yield analysis. The planning needs to include how and what patterns to generate during ATPG/DFT, what design data to archive, how to optimize your test program, how much data to collect, and what/how much diagnosis to perform. This white paper will address how to optimize the test environment in order to enable efficient diagnosis-driven yield analysis.

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Defects and Defect Detection Industry Trends

Posted in: Silicon Learning

This white paper describes the known common manufacturing defects and methods for detecting defects.

At design nodes smaller than 90 nm, manufacturing test challenges grow exponentially as compared to larger design nodes. At larger design nodes, manufacturing defects were typically a bridge or open that could be detected using a stuck-at tests. At smaller design nodes defects that effect at-speed performance are becoming more common and slow speed testing will not detect them.

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Faster Time to Root Cause with Diagnosis-Driven Yield Analysis

Posted in: Silicon Learning

This whitepaper describes the benefits of implementing a diagnosis-driven yield analysis flow using the Tessent® Diagnosis and Tessent YieldInsight® software products.

Abstract: ICs developed at advanced technology nodes of 65 nm and below exhibit an increased sensitivity to small manufacturing variations. New design-specific and feature-sensitive failure mechanisms are on the rise. Complex variability issues that involve interactions between process and layout features can mask systematic yield issues. Without improved yield analysis methods, time-to-volume is delayed, mature yield is suboptimal, and product quality may suffer, thereby threatening a manufacturer’s profitability. Diagnosis-driven yield analysis is a methodology that leverages production test results, volume scan diagnosis, and statistical analysis to identify the cause of yield loss prior to failure analysis. This methodology can reduce the root cause cycle time with 75-90%. The methodology can be expanded with DFM-aware yield analysis to help separate design and process related yield limiters.

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