Image Analytics for Clog Detection in Substrate Processing Equipment
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Solution Overview
Problem
Conventional methods for detecting clogs in substrate processing equipment parts, such as showerheads, are time-consuming, inaccurate, and subjective, leading to production of substrates with performance data that does not meet threshold values.
Innovation Solution
A method using image analytics to identify and detect clogs in substrate processing equipment parts by analyzing images of the parts, determining neighboring angular distances and areas of holes, and identifying subsets of holes that are at least partially clogged, thereby facilitating corrective actions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods are used for detecting clogs in substrate processing equipment parts, then the detection process is simple to implement, but the detection accuracy is low and the process is time-consuming
Solution Approach 1:
The patent replaces conventional mechanical or manual inspection methods with an optical imaging system. The system captures images of the substrate processing equipment part and uses image processing algorithms to automatically detect clogs in holes, eliminating the need for time-consuming manual inspection while significantly improving detection accuracy through objective image-based analysis.
Solution Approach 2:
The patent creates a digital copy (image) of the physical substrate processing equipment part. By analyzing this optical copy through image processing, the system can detect clogs without physically contacting or manipulating the actual part, thereby reducing detection time while maintaining high accuracy through detailed image analysis of hole patterns and clog characteristics.
2Measurement precision
If conventional clog detection methods are used, then the equipment structure remains simple, but the detection results are subjective and inaccurate
Solution Approach 1:
The patent replaces subjective human judgment with objective image processing algorithms. The system automatically analyzes captured images to detect clogs, eliminating subjectivity in detection results. Although this increases device complexity by introducing imaging and processing components, it achieves significantly more reliable and consistent detection outcomes.
Solution Approach 2:
The patent introduces an intermediary image processing system between the physical equipment part and the detection conclusion. The image analytics system serves as an objective mediator that translates visual information into quantifiable detection results, removing human subjectivity from the evaluation process while providing clear, actionable insights about clog conditions.
3Manufacturing precision
If manual inspection methods are used for clog detection, then the system complexity is low, but the detection is subjective and leads to production of substrates that do not meet performance thresholds
Solution Approach 1:
The patent replaces manual inspection with automated image analytics to ensure consistent detection quality. This substitution eliminates the subjectivity that previously led to missed clogs and subsequent substrate performance issues. The increased system complexity is justified by the significant improvement in substrate quality assurance and the prevention of defective product production.
Solution Approach 2:
The patent performs clog detection before substrate production using image analytics. By identifying clogs in advance through objective image analysis, the system prevents defective substrates from being produced in the first place. This preliminary detection approach, though requiring more complex equipment, ensures that only properly functioning equipment produces substrates, thereby guaranteeing performance quality.
4Productivity
If conventional detection methods are used, then the operational simplicity is maintained, but production throughput is reduced due to time-consuming detection and frequent interruptions
Solution Approach 1:
The patent replaces slow manual inspection with rapid automated image capture and analysis. The imaging system can quickly capture and process images of equipment parts, identifying clogs in seconds rather than minutes or hours. This dramatic speed increase, achieved through automated optical systems, directly boosts production throughput by minimizing detection time and reducing production interruptions.
Solution Approach 2:
The patent enables continuous or near-continuous monitoring of equipment parts for clogs using the image analytics system. Rather than stopping production for manual inspections, the automated system can quickly assess equipment status, allowing production to continue with minimal interruptions. This continuity of production activity significantly improves overall throughput despite the added system complexity.
Data Source
AI summary
A method includes determining, by a processing device based on an image of a substrate processing equipment part that forms holes, a clockwise holes spiral and an anti-clockwise holes spiral of the holes. The method further includes identifying, by the processing device, a first subset of the holes in at least one of the clockwise holes spiral or the anti-clockwise holes spiral that are at least partially clogged. A corrective action associated with the substrate processing equipment part is to be performed based on the first subset of the holes that are at least partially clogged.