Substrate Processing Abnormality Detection via Operation Value Correlation
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Solution Overview
Problem
Substrate processing apparatuses face challenges in detecting abnormalities early enough to prevent equipment damage or deterioration, as existing methods rely on monitoring individual component states without considering correlations between operation values.
Innovation Solution
A substrate processing apparatus and method that acquire and correlate operation values from multiple components, such as flow rates and pressures, to detect abnormalities based on defined allowable ranges and statistical analysis, enabling early detection of issues before they lead to failure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If monitoring is performed on individual component states separately, then the monitoring system is simple to implement, but abnormalities cannot be detected early enough to prevent equipment damage
Solution Approach 1:
The patent combines multiple operation values from different components into a unified monitoring system that evaluates correlations between parameters. Instead of monitoring each component separately, the system integrates data from multiple sources (e.g., temperature, pressure, flow rate) and analyzes their interrelationships to detect abnormalities early, resolving the contradiction between detection capability and system complexity.
Solution Approach 2:
The system continuously monitors operation values, compares them against reference ranges, and provides feedback when correlations deviate from normal patterns. This feedback mechanism enables early abnormality detection by identifying subtle changes in parameter relationships before they lead to equipment failure, while maintaining a manageable monitoring framework through automated threshold-based alerts.
2Measurement precision
If correlation analysis between multiple operation values is performed, then early abnormality detection is enabled, but the analysis complexity and computational load increase
Solution Approach 1:
The patent transforms complex correlation analysis into simplified parameter comparisons by establishing reference ranges for operation values and their relationships. Instead of performing continuous complex mathematical correlation analysis, the system converts multi-parameter relationships into comparable metrics against predefined thresholds, maintaining high detection precision while reducing computational complexity.
Solution Approach 2:
The system performs preliminary analysis during normal operation to establish reference ranges and expected correlation patterns. By pre-characterizing normal operation parameters and their relationships, the system reduces real-time analysis complexity, as abnormality detection then becomes a matter of comparing current values against established benchmarks rather than performing complex real-time correlation calculations.
3Reliability
If continuous monitoring of multiple parameters is implemented, then early detection accuracy improves, but the time and computational resources required increase
Solution Approach 1:
The system implements selective monitoring by focusing on key operation values and their correlations that are most indicative of potential abnormalities. Rather than continuously analyzing all possible parameters at full depth, the system monitors critical parameters with higher frequency and importance, achieving reliable early detection while optimizing the use of time and computational resources through prioritized analysis.
Data Source
AI summary
In a substrate processing apparatus, a substrate is processed with use of a processing liquid. A first operation component and a second operation component are used in the substrate process. A first operation value of the first operation component and a second operation value of the second operation component are acquired by an operation value acquirer. Whether an abnormality has occurred is determined by an abnormality determiner based on the correlation between the first operation value and the second operation value that are acquired by the operation value acquirer.