Pattern Density Analysis for IC Layout Extreme Values
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Solution Overview
Problem
Traditional pattern density analysis methods fail to accurately calculate local pattern densities, especially missing features that result in errors and omissions, particularly in regions with extreme density values, which can lead to deviations in etching and grinding processes.
Innovation Solution
A pattern density analysis method that constructs inspection windows based on layout pattern attributes, using first and second relevant windows to accurately determine maximum and minimum local pattern densities, thereby avoiding errors and omissions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional fixed-step inspection window method is used, then the analysis process is simple, but the measurement precision of local pattern density is poor and extreme values are missed
Solution Approach 1:
The patent applies preliminary action by first identifying all pattern elements and their positions before constructing inspection windows. The system pre-processes the layout data to extract pattern attributes (position, size, shape) and stores them in a data structure that enables efficient window construction. This preliminary preparation allows the system to accurately capture extreme density regions without requiring complex real-time calculations during the actual density measurement process.
Solution Approach 2:
The patent segments the layout into discrete pattern elements and divides the inspection process into multiple overlapping inspection windows of fixed size. Each window independently calculates pattern density based on the patterns it contains. This segmentation approach allows the system to systematically cover the entire layout while maintaining simple, standardized calculation procedures for each segment, thereby achieving high measurement precision without excessive overall complexity.
2Reliability
If fixed-step inspection window method is used, then the calculation process is simple, but the reliability of density analysis is reduced due to missed features
Solution Approach 1:
The patent implements feedback by comparing the calculated pattern density in each inspection window against pre-established threshold values and design rules. When a window's density falls outside acceptable ranges or when extreme values are detected, the system generates feedback signals that trigger re-examination of adjacent regions and initiate corrective actions. This feedback mechanism ensures reliable detection of density anomalies while maintaining efficient processing by focusing computational resources only on problematic areas rather than re-analyzing the entire layout.
Solution Approach 2:
The patent introduces dynamic adjustment of inspection window parameters based on detected pattern characteristics. When high-density or low-density regions are identified, the system dynamically modifies window size, step size, or detection sensitivity to better capture extreme values. This dynamic approach enhances reliability by adapting to local layout characteristics while preserving productivity through targeted adjustments rather than comprehensive re-analysis of the entire design.
3Manufacturing precision
If traditional inspection window method is used, then the operation is simple, but the manufacturing precision of etching and grinding processes is compromised
Solution Approach 1:
The patent replaces manual, mechanical inspection procedures with an automated computer-based system that uses digital image processing and algorithmic analysis. The system automatically extracts pattern data, constructs inspection windows, calculates densities, and identifies extreme values without requiring manual intervention. This substitution maintains operational simplicity from the user perspective while dramatically improving manufacturing precision by eliminating human error and enabling sub-pixel accuracy in density measurement, thereby providing more reliable guidance for etching and grinding process control.
Data Source
AI summary
The present disclosure provides a pattern density analysis method for analyzing a local pattern density of a layout, the method comprising: obtaining a pattern attribute of each layout pattern located on a layout region to be analyzed; setting, for each layout pattern, a relevant window for the layout pattern based on the corresponding pattern attribute; calculating the pattern density of each relevant window; and selecting the maximum value of the pattern densities of the relevant windows as the maximum local pattern density of the layout, and selecting the minimum value of the pattern densities of the relevant windows as the minimum local pattern density of the layout.