Process Profile Shape Analysis for Automatic End Point Detection
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Solution Overview
Problem
Existing methods for determining the end point of a dynamic process, such as a blending process, are inaccurate and subjective due to the difficulty in selecting appropriate thresholds and the reliance on visual inspection, particularly when multiple iterations are required.
Innovation Solution
A method and device that generate a process profile and slope profile from spectroscopic data, identify a set of slope thresholds based on the trend, and determine the end point of the dynamic process without the need for calibration or historical data, using a moving block analysis to eliminate subjectivity and improve reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual inspection and manual threshold selection are used to determine the end point of a dynamic process, then the method is simple to implement, but the measurement precision and reliability are poor due to subjectivity
Solution Approach 1:
The patent replaces manual visual inspection with an automated computational system that uses spectroscopic data processing, slope calculation, and threshold-based detection algorithms to objectively determine the end point of dynamic processes, eliminating human subjectivity while maintaining operational simplicity
Solution Approach 2:
The system performs self-calibration and automatic threshold determination by analyzing the process profile shape and slope characteristics, eliminating the need for manual calibration or historical data while achieving high measurement precision through self-contained analytical capabilities
2Reliability
If manual threshold selection and visual inspection are used, then calibration and historical data are not required, but the reliability and consistency of end point detection are poor
Solution Approach 1:
The patent transforms the end point detection problem by changing from fixed threshold parameters to dynamic slope-based parameters that adapt to the process profile shape, improving reliability by capturing the actual process behavior rather than relying on predetermined values
Solution Approach 2:
The system performs preliminary analysis of the process profile to automatically determine appropriate slope thresholds before making the end point determination, ensuring reliable detection without requiring pre-calibration or historical data while maintaining ease of operation
3Productivity
If multiple iterations of a dynamic process are required, then the process can be optimized, but the time required for accurate end point determination increases due to repeated visual inspection
Solution Approach 1:
The patent replaces repeated manual visual inspection across multiple iterations with an automated algorithm that rapidly processes spectroscopic data and determines end points objectively, significantly reducing the time required for each iteration while maintaining or improving process optimization
Solution Approach 2:
The system enables continuous automated monitoring and detection across multiple process iterations without interruption or manual intervention, maintaining constant productivity while eliminating the time loss associated with repeated visual inspections and manual threshold adjustments
Data Source
AI summary
In some implementations, a device may receive spectroscopic data associated with an iteration of a dynamic process. The device may generate, based on the spectroscopic data, a process profile associated with the iteration of the dynamic process. The device may generate, based on the process profile, a slope profile associated with the iteration of the dynamic process. The device may determine a trend of the process profile. The device may identify a set of slope thresholds associated with the iteration of the dynamic process based on the trend.