Wafer Defect Detection Using Pattern-Matched Database Weights
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Solution Overview
Problem
As semiconductor manufacturing processes approach their performance limits, detecting smaller defects on wafers becomes increasingly difficult due to the growing population of both yield-relevant and nuisance defects, making it challenging to maintain high manufacturing yields and profitability.
Innovation Solution
A method and system for detecting defects on wafers using a searchable database that assigns values to design patterns, synchronizes database searches with wafer inspection output, and applies defect detection algorithms to identify defects based on pattern matching, enhancing sensitivity and efficiency through ultrafast pattern search capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If design rules are shrunk to increase device density, then manufacturing precision is improved, but defect detection precision deteriorates due to increased noise from nuisance defects
Solution Approach 1:
The patent applies local quality by assigning different weights to different spatial locations on the wafer based on design pattern characteristics. Regions with identical or similar patterns are grouped together and assigned the same weight, while different pattern regions receive different weights. This allows the inspection system to adaptively emphasize or de-emphasize specific areas based on their defect sensitivity, thereby maintaining high measurement precision even as device dimensions shrink.
Solution Approach 2:
The patent changes the parameter of defect weighting by dynamically adjusting weights based on design pattern matching. Instead of using uniform weighting, the system calculates weights for different wafer regions by comparing their patterns against a database of known patterns. This parameter change enables the system to distinguish between yield-relevant defects and nuisance defects, maintaining detection precision despite increased defect populations from scaled-down design rules.
2Measurement precision
If inspection sensitivity is increased to detect smaller defects, then defect detection precision is improved, but the number of false positives increases due to nuisance defects
Solution Approach 1:
The patent reduces false positives by applying location-dependent weighting where each wafer region is weighted according to its pattern characteristics. Regions with patterns known to generate nuisance defects are assigned lower weights, while regions with critical patterns receive higher weights. This local differentiation allows the system to maintain high sensitivity for detecting true defects while suppressing false alarms from nuisance defects.
Solution Approach 2:
The patent converts the harmful effect of nuisance defects into a benefit by using pattern matching to identify and weight regions based on their likelihood to produce false positives. By analyzing design patterns and assigning appropriate weights, the system transforms the presence of nuisance defects into an opportunity to refine defect classification, thereby improving overall detection accuracy while reducing false positives.
3Device complexity
If traditional inspection methods are used without design data integration, then device complexity is reduced, but defect detection precision deteriorates due to inability to distinguish yield-relevant defects from nuisance defects
Solution Approach 1:
The patent applies preliminary action by pre-processing design data into a weighted database before inspection. Design patterns are analyzed in advance, weights are calculated and stored, and this pre-computed information is then applied during inspection to automatically differentiate between yield-relevant and nuisance defects. This preliminary preparation enables the inspection system to achieve high detection precision without adding significant operational complexity.
Solution Approach 2:
The patent introduces design pattern data as an intermediary between the inspection system and the wafer defects. This intermediary layer provides contextual information that enables the system to intelligently distinguish between different defect types. By matching observed defects against the pre-processed design pattern database, the system achieves high detection precision while maintaining relatively simple inspection operations.
Data Source
AI summary
Methods and systems for detecting defects on a wafer are provided. One method includes creating a searchable database for a design for a wafer, which includes assigning values to different portions of the design based on patterns in the different portions of the design and storing the assigned values in the searchable database. Different portions of the design having substantially the same patterns are assigned the same values in the searchable database. The searchable database is configured such that searching of the database can be synchronized with generation of output for the wafer by one or more detectors of a wafer inspection system. Therefore, as the wafer is being scanned, design information for the output can be determined as fast as the output is generated, which enables multiple, desirable design based inspection capabilities.