Automated Optical Bump Height Measurement
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Solution Overview
Problem
Current 3-D measurement techniques for wafers during fabrication are manual, time-consuming, and prone to errors, lacking efficiency and reliability, especially in detecting surface features and thicknesses of semi-transparent and metal layers.
Innovation Solution
An automated optical microscope system that varies the distance between the sample and the objective lens at predetermined steps, captures images, determines characteristic values, and compares them to identify focused surfaces, allowing for precise measurement of surface distances and layer thicknesses using peak and range mode operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual microscope operation is used to gather 3-D measurement information, then human users can determine focus using their eyes, but the process is time-consuming and prone to errors
Solution Approach 1:
The patent replaces manual mechanical microscope operation with an automated optical measurement system that uses light reflection characteristics and image processing to automatically determine surface focus and 3-D measurements, eliminating human eye-based focusing while maintaining or improving measurement accuracy
Solution Approach 2:
The system performs self-measurement by automatically capturing images at multiple distances, analyzing reflection characteristics, determining which images are in focus, and calculating 3-D information without human intervention, making the measurement process autonomous and efficient
2Measurement precision
If automated image capture at multiple distances is performed, then 3-D information can be generated accurately, but the system complexity increases
Solution Approach 1:
The measurement process is segmented into discrete distance steps where images are captured at predetermined intervals, allowing the system to systematically explore the depth range and identify focused surfaces through controlled segmentation of the measurement space
Solution Approach 2:
The patent introduces light reflection characteristics as an intermediary parameter that mediates between the optical system and the sample surface, using the reflection properties to automatically determine which images are in focus and to extract 3-D information without direct mechanical contact or complex positioning
3Extent of automation
If characteristic values of pixels are analyzed to identify focused surfaces, then automated surface detection is achieved, but processing complexity increases
Solution Approach 1:
The system exploits changes in pixel characteristic values (analogous to color/intensity changes) that occur when surfaces come into focus, using these optical signal variations to automatically identify focused images and extract surface information through analysis of reflection intensity patterns
Solution Approach 2:
The patent analyzes characteristic values of pixels to determine which images are in focus, using partial information (key pixel characteristics) rather than processing all image data, thereby achieving automated surface detection with reduced processing complexity compared to full image analysis
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
Enables fast, reliable, and accurate 3-D information generation, reducing human intervention and improving the detection of wafer defects and layer thicknesses, enhancing the efficiency of wafer fabrication processes.
Implementation Method 1
capturing an image at each pre-determined step; determining a characteristic value of each pixel in each captured image
Data Source
AI summary
A method of generating 3D information including: varying the distance between the sample and an objective lens of the optical microscope at pre-determined steps; capturing an image at each pre-determined step; determining a characteristic value of each pixel in each captured image; determining, for each captured image, the greatest characteristic value across a first portion of pixels in the captured image; comparing the greatest characteristic value for each captured image to determine if a surface of the sample is present at each pre-determined step; determining a first captured image that is focused on an apex of a bump of the sample; determining a second captured image that is focused on a first surface of the sample based on the characteristic value of each pixel in each captured image; and determining a first distance between the apex of the bump and the first surface.