Ultrasonic Inspection of Semiconductor and MEMS Wafers
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Solution Overview
Problem
Existing ultrasonic inspection methods struggle to detect fine defects in multi-layer semiconductor and MEMS wafers with complex patterns, as they often confuse defects with normal patterns, especially in miniaturized and mini-functionalized products, due to the difficulty in visually distinguishing between them.
Innovation Solution
The method involves obtaining an image of the inspection object, generating a reference image without defects, creating a multi-value mask to differentiate non-defective pixels, calculating defect accuracy by matching the brightness of the object image with the reference image, and comparing this accuracy with the mask to detect defects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If visual inspection method is used to detect defects, then inspection speed is fast, but detection precision deteriorates due to inability to distinguish fine defects from normal patterns
Solution Approach 1:
The patent segments the inspection image into multiple regions based on pattern types (first pattern regions and second pattern regions). By dividing the complex multi-layer structure into manageable segments with different evaluation criteria, the system can accurately detect defects in each region without being overwhelmed by the overall complexity, thus improving detection precision while maintaining automated high-speed inspection.
Solution Approach 2:
The patent applies different evaluation methods to different regions: using reflection intensity evaluation for first pattern regions and contour shape evaluation for second pattern regions. This local quality approach tailors the inspection strategy to the specific characteristics of each pattern type, enabling accurate defect detection in diverse structural contexts without compromising inspection speed.
2Productivity
If automated defect detection is implemented, then productivity increases, but device complexity increases due to need for complex image processing algorithms
Solution Approach 1:
The patent divides the automated inspection process into distinct segments: region segmentation based on pattern types, separate evaluation processes for different regions, and hierarchical defect determination. This segmentation simplifies the overall complex algorithm by breaking it into manageable modules, making the automated system more implementable while maintaining high productivity.
Solution Approach 2:
Instead of attempting to detect all defects uniformly across the entire image using a single complex algorithm, the patent inverts the approach by first segmenting the image into regions with different characteristics, then applying simplified region-specific evaluation methods. This inversion reduces overall system complexity while maintaining automated inspection capability.
3Reliability
If multi-layer structure inspection is performed, then detection of internal defects is enabled, but measurement precision deteriorates due to pattern complexity and signal interference
Solution Approach 1:
The patent segments the multi-layer structure into distinct pattern regions (first and second patterns) and applies region-specific evaluation criteria. This segmentation allows the system to isolate defect signals from the complex multi-layer background by evaluating each region according to its specific characteristics, thereby improving measurement precision in internal defect detection.
Solution Approach 2:
The patent applies different evaluation qualities to different regions: reflection intensity evaluation for regions where intensity variation is the primary defect indicator, and contour shape evaluation for regions where shape deviation is more significant. This local quality approach enhances the ability to distinguish true defect signals from normal pattern variations in the multi-layer structure.
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 enables the detection of fine defects within complex patterns on semiconductor and MEMS wafers by segmenting images into pattern groups, allowing for high-sensitivity detection of internal defects within a wide inspection range, effectively distinguishing between normal patterns and defects.
Implementation Method 1
The ultrasonic wave propagates through a liquid or solid material and generates a reflected wave at an interface between materials having different acoustic impedances or at a cavity.
Implementation Method 2
a reflection property due to difference in acoustic impedance is generally used
Data Source
AI summary
In an ultrasonic inspection performed on an inspection object including a fine and multi-layer structure such as a semiconductor wafer and a MEMS wafer, a defect is detected by: separating a defect present inside from a normal pattern; obtaining an image of the inspection object by imaging the inspection object having a pattern formed thereon to enable a highly sensitive detection; generating a reference image that does not include a defect from the obtained image of the inspection object; generating a multi-value mask for masking a non-defective pixel from the obtained image of the inspection object; calculating a defect accuracy by matching the brightness of the image of the inspection object and the reference image; and comparing the calculated defect accuracy with the generated multi-value mask.