Imaging Substrate Misalignment Detection via Pixel Analysis
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Solution Overview
Problem
In semiconductor manufacturing, substrate misalignment due to degraded or uneven substrate supports can lead to non-uniform processing, contamination, and damage, as well as limitations in layer stacking, due to thermal gradients and stress caused by improper alignment and handling.
Innovation Solution
A method and apparatus using imaging techniques, such as a camera, to detect misalignment by calculating center of gravity and average weight values of pixels in images of the substrate and support structures, allowing for correction of positional errors and preventing contamination and non-uniform processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If substrate support structures are used to hold substrates during processing, then substrate stability is improved, but misalignment and contamination occur due to degradation and improper alignment over time
Solution Approach 1:
The imaging system captures images of the substrate and support structures before processing begins, allowing misalignment to be detected and corrected in advance. This preliminary detection prevents misalignment-related contamination during processing, as the system identifies positional errors before the substrate is firmly attached to the support structure.
Solution Approach 2:
The system uses imaging feedback to monitor the position of substrates and support structures. By continuously or periodically capturing images and analyzing pixel data to calculate center of gravity values, the system provides feedback on alignment status, enabling real-time detection and correction of misalignment issues that would otherwise lead to contamination.
2Adaptability or versatility
If substrates are transferred between multiple chambers, then processing versatility is improved, but significant slippage and contamination occur due to improper alignment between support structures
Solution Approach 1:
Before substrate transfer between chambers, the imaging system captures images to detect misalignment between support structures. This preliminary detection allows the system to identify alignment issues before the transfer operation begins, preventing slippage and contamination that would occur during improper transfer operations.
Solution Approach 2:
The imaging system provides feedback on the alignment status between different chamber support structures. By analyzing pixel data and calculating center of gravity values, the system monitors whether substrates are properly aligned during transfer operations, enabling real-time detection of misalignment that would cause slippage and contamination between chambers.
3Measurement precision
If imaging techniques are used to detect misalignment, then measurement precision is improved, but device complexity increases due to additional imaging equipment and processing requirements
Solution Approach 1:
The system replaces complex mechanical alignment measurement devices with optical imaging technology. Instead of using mechanical sensors or complex measurement apparatus, the patent uses standard imaging equipment to capture pictures of substrates and support structures, then processes the images computationally to detect misalignment with high precision.
Solution Approach 2:
The imaging system creates optical copies (images) of the substrate and support structures, which can then be analyzed without physically touching or disturbing the actual components. This allows for non-contact, high-precision measurement of alignment status, reducing the need for complex physical measurement devices while maintaining detection accuracy.
Data Source
AI summary
A method and apparatus for detecting substrate misalignment (i.e., position displacement error) and/or substrate support misalignment. According to certain aspects, a method for detecting a misalignment of an object in a processing system is provided. The method generally includes obtaining a first image of the object, determining first values associated with pixels in at least one region of the first image, calculating at least one of a center of gravity value of the pixels in the at least one region or an average weight of the pixels in the at least one region, and detecting a misalignment of the object based on at least one of the calculated center of gravity or average weight of the pixels in the at least one region.