Transparent Wafer Defect Detection With Chuck Pattern Suppression

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Solution Overview

Problem

Existing defect detection systems struggle to effectively distinguish defects on transparent or translucent wafers due to interference from chuck components, leading to poor sensitivity and throughput, especially when chuck patterns and surface roughness obscure defects.

Innovation Solution

A two-step defect detection method using local reference pixels within the same die, combining mean and median calculations to enhance sensitivity and speed, and independent bright and dark field channel analysis to suppress chuck patterns and improve defect detection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional defect detection algorithms are used on transparent or translucent wafers, then the system can process images, but the chuck components (patterns and surface roughness) obscure the defects, leading to poor detection sensitivity

Engineering Contradiction:
Improvedefect detection sensitivityVSAvoidchuck pattern interference
Core Design Contradiction:
Measurement precisionVSObject-affected harmful factors

Solution Approach 1:

The patent divides the defect detection process into two separate channels: bright field imaging for detecting chuck patterns and dark field imaging for detecting defects. This segmentation allows each channel to specialize in detecting specific features, preventing the chuck patterns from obscuring the defects in the final detection result.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediary processing step where the bright field image (containing chuck patterns) is used to generate a mask or reference that is then applied to the dark field image. This intermediary step effectively removes or suppresses the chuck pattern interference before defect detection occurs.

Inventive Principle:
Principle #24Intermediary (Mediator)

2Productivity

If existing defect detection tools are used to achieve defect detection on transparent wafers, then some defects can be detected, but the throughput and inspection sensitivity targets cannot be met due to the need for complex image processing

Engineering Contradiction:
Improveinspection throughputVSAvoidimage processing complexity
Core Design Contradiction:
ProductivityVSDevice complexity

Solution Approach 1:

The patent segments the imaging system into two parallel channels (bright field and dark field) that operate simultaneously. This allows defect detection to proceed without requiring complex sequential image processing, as each channel provides complementary information that can be combined through simple logical operations, thereby maintaining high throughput.

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent changes the imaging parameters by using two different field conditions (bright and dark) rather than relying on a single imaging mode. This parameter change enables the system to detect both chuck patterns and defects efficiently without increasing processing complexity, as the dual-channel approach processes images in parallel rather than requiring complex sequential analysis.

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentEP3646372B1Defect detection on transparent or translucent wafers
Publication Date: 2025.10.01 KLA CORP
  • EP3646372B1 patent drawingFigure 1
  • EP3646372B1 patent drawingFigure 2
  • EP3646372B1 patent drawingFigure 3

AI summary

Defect detection on transparent or translucent wafers can be performed on a die using references from the same die. A first calculated value based on a kernel size, such as a moving mean, is determined. A first difference is determined by subtracting the first calculated value from a pixel intensity. Candidate pixels with a first difference above a threshold are classified. A second calculated value based on a kernel size, such as a local median, is determined. A second difference is determined by subtracting the second calculated value from the pixel intensity. Pixels that include a defect are classified when the second difference is above the threshold.