Semiconductor Defect Inspection Using Acoustic and Optical Screening
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Solution Overview
Problem
Defect inspection in semiconductor devices is time-consuming and costly, necessitating more efficient methods and systems.
Innovation Solution
A system and method utilizing a C-mode scanning acoustic microscope and optical sensors to detect defects in semiconductor wafers, including hybrid bonding techniques and image processing to identify and analyze defect features, such as defect position, perimeter, area, and size, with threshold criteria for defect identification and scrap determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image processing is used for defect inspection in semiconductor devices, then measurement precision is improved, but loss of time increases and productivity decreases
Solution Approach 1:
The patent performs preliminary defect detection using acoustic microscopy before final quality assurance stages. By conducting initial screening with acoustic waves to identify defective regions, the system prepares information in advance that guides subsequent optical inspection, reducing the time needed for comprehensive defect analysis while maintaining high precision.
Solution Approach 2:
The inspection process is divided into multiple stages: initial acoustic microscopy screening to identify defective regions, followed by targeted optical inspection of specific areas. This segmentation allows the system to apply different detection methods to different regions, improving overall efficiency without sacrificing detection precision.
2Measurement precision
If comprehensive image processing is performed for defect inspection, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent combines acoustic microscopy and optical inspection systems into an integrated defect detection platform. By merging these two complementary techniques, the system achieves comprehensive defect detection capability while sharing common control and processing infrastructure, thereby improving precision without proportionally increasing overall system complexity.
Solution Approach 2:
The system uses acoustic microscopy as an intermediary screening tool that identifies defective regions before optical inspection. This intermediary step provides targeted information that simplifies the subsequent optical analysis, reducing the computational complexity required for comprehensive defect detection while maintaining high measurement precision.
3Reliability
If traditional defect inspection methods are used, then reliability is maintained, but productivity decreases and loss of time increases
Solution Approach 1:
The system performs preliminary acoustic microscopy screening to identify defective dies before final quality assurance. This preliminary action filters out obviously defective regions, allowing the reliable but time-consuming optical inspection to focus only on critical areas, thereby maintaining quality assurance reliability while significantly improving inspection throughput.
Solution Approach 2:
The inspection workflow is segmented into rapid acoustic screening followed by detailed optical analysis of suspicious regions. This segmentation enables the system to maintain high reliability through comprehensive optical verification while improving productivity by avoiding redundant detailed analysis of obviously defective or normal regions identified in the acoustic screening stage.
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
Enhances defect detection precision and efficiency, reducing costs by identifying defects before final quality assurance stages and improving semiconductor device quality.
Implementation Method 1
A system and method utilizing a C-mode scanning acoustic microscope and optical sensors to detect defects in semiconductor wafers
Data Source
AI summary
A method and a system for detecting a semiconductor device are provided. The method comprises obtaining an image of the semiconductor device, evaluating a feature of the image, detecting a defect of the semiconductor device based on the feature, extracting a defect information for the defect, calculating a defect die ratio (DDR) in response to the defect and analyzing a relation between the DDR and the defect information.