Dynamic Design Attributes for Wafer Inspection Binning
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Solution Overview
Problem
As semiconductor design rules shrink, wafer inspection systems become overwhelmed by nuisance defects, reducing sensitivity and increasing costs due to the need to filter out non-critical defects, which limits their ability to detect subtle design-for-manufacturability defects effectively.
Innovation Solution
Implementing a dynamic design attributes concept in wafer inspection tools that allows users to define and calculate design attributes at runtime, enabling the creation of custom formulae for binning defects based on design data, thereby enhancing defect sorting and classification capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If inspection sensitivity is increased to detect subtle DFM defects, then measurement precision is improved, but the system becomes overwhelmed by nuisance defects increasing data processing load and reducing throughput
Solution Approach 1:
The patent segments defects into different categories (nuisance defects vs. critical DFM defects) using design attribute-based binning. By dividing the defect population into segments with different characteristics, the system can apply different processing strategies to each segment, allowing high sensitivity inspection while managing data processing load through selective filtering of nuisance defect segments.
2Measurement precision
If inspection sensitivity is increased to detect subtle DFM defects, then measurement precision is improved, but data processing capacity is overwhelmed requiring extensive filtering
Solution Approach 1:
The patent performs preliminary action by calculating design attributes and creating defect bins before the actual defect analysis process. Design attribute formulas are established in advance, and defects are pre-categorized into bins based on their design attributes. This preliminary binning reduces the complexity of subsequent data processing by organizing defects into manageable groups that can be analyzed more efficiently.
3Productivity
If design rules are shrunk to increase device density, then productivity is improved, but the population of nuisance defects increases dramatically
Solution Approach 1:
The patent applies local quality by using design attribute-based binning to treat different defect populations differently. Instead of applying a uniform filtering approach, the system calculates specific design attributes (such as pattern density, feature size, etc.) for different regions and defect types, and applies appropriate binning strategies locally. This allows the system to manage nuisance defects in high-density areas while maintaining sensitivity for critical defects.
4Device complexity
If fixed defect binning parameters are used, then device complexity is reduced, but adaptability to different design rules and defect patterns is limited
Solution Approach 1:
The patent implements dynamics by allowing defect binning parameters to be dynamic rather than fixed. The system calculates design attributes based on actual wafer inspection data and adjusts binning parameters dynamically to adapt to different design rules, defect patterns, and process conditions. This dynamic approach maintains relative simplicity while providing high adaptability through formula-based parameter adjustment.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides users with greater control and flexibility to derive design attributes dynamically, improving the separation of nuisance defects from critical ones, enhancing the sensitivity of the inspection system, and reducing the burden on data processing capacity.
Implementation Method 1
scanning at least a portion of the wafer with the wafer inspection tool thereby generating output responsive to light from at least a portion of the wafer
Data Source
AI summary
Methods and systems for dynamic design attributes for wafer inspection are provided. One method includes, at run time of a wafer inspection recipe, prompting a user of a wafer inspection tool on which the wafer inspection recipe is performed for information for a design based binning (DBB) process. The information includes one or more formulae for calculating design attributes from a design for a wafer. The design attributes are used to bin the defects in the DBB process. The method also includes performing inspection of a wafer according to an updated wafer inspection recipe. Performing the inspection includes binning defects detected on the wafer according to the DBB process in the updated wafer inspection recipe.