GDS-Assisted Fault Localization for Systematic PFA Hotspots
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Solution Overview
Problem
Conventional physical failure analysis (PFA) techniques struggle to precisely locate systematic faults in semiconductor dies due to the inability to accurately identify failure regions, necessitating time-intensive manual processes over large areas.
Innovation Solution
A systematic fault localization system utilizing GDS-assisted cross-layer pattern decomposition and normalized differential analysis to identify systematic hotspots within sub-regions of semiconductor dies, reducing the search area by 5000x and enhancing precision.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional PFA techniques are used to identify failure regions, then failure analysis can be performed, but the search area is large and localization precision is poor
Solution Approach 1:
The patent segments the large failure region into multiple sub-regions by dividing the die into a grid structure and analyzing each sub-region independently. This segmentation allows precise localization of faults within specific sub-regions rather than treating the entire failure area as a single region, directly resolving the contradiction between large search area and poor localization precision.
2Reliability
If manual net tracing and physical sample analysis are performed over large regions, then root cause can be determined, but the process is time-intensive
Solution Approach 1:
The patent performs preliminary automated analysis of electrical test data and GDS layout information to identify and localize failure regions before physical sample preparation. By pre-localizing faults to specific sub-regions using computational methods, the patent eliminates the need for time-consuming manual net tracing and reduces physical analysis to only the identified sub-regions, thereby maintaining root cause identification accuracy while dramatically reducing PFA cycle time.
Solution Approach 2:
The patent replaces manual mechanical processes (manual net tracing, physical delayering) with automated computational analysis of electrical test data and GDS files. This substitution uses software-based pattern recognition and data processing to identify failure regions, replacing time-intensive human-operated mechanical procedures while maintaining or improving identification accuracy.
3Adaptability or versatility
If conventional techniques are used, then failure analysis can proceed, but engineer judgment is required for sample selection
Solution Approach 1:
The patent implements self-service by enabling the system to automatically select PFA samples based on computational analysis of test data and layout information. The automated sample selection process identifies representative failures and localizes them to specific sub-regions without requiring engineer judgment, thereby reducing device complexity and manual intervention while maintaining the adaptability to handle various failure types through algorithmic pattern recognition.
Data Source
AI summary
Systematic fault localization systems and methods are provided which utilize computational GDS-assisted navigation to accelerate physical fault analysis to identify systematic fault locations and patterns. In some embodiments, a method includes detecting a plurality of electrical fault regions of a plurality of dies of a semiconductor wafer. Decomposed Graphic Database System (GDS) cross-layer clips are generated which are associated with the plurality of electrical fault regions. A plurality of cross-layer common patterns is identified based on the decomposed GDS cross-layer clips. Normalized differentials may be determined for each of the cross-layer common patterns, and locations of hotspots in each of the dies may be identified based on the determined normalized differentials.