Semiconductor Tool Abnormality Detection via Correlation Slope
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Solution Overview
Problem
Existing semiconductor manufacturing apparatuses lack an efficient method to detect abnormalities in real-time, which can lead to equipment failures and production downtime.
Innovation Solution
An abnormality detecting apparatus that generates correlation data from sensor values of a first and second monitoring target, calculates the slope of a regression line from this data, and determines abnormalities based on predefined control values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If real-time monitoring of multiple parameters is implemented, then abnormality detection capability is improved, but device complexity increases
Solution Approach 1:
The patent combines multiple monitoring targets into a single correlation analysis system. Instead of independently monitoring each parameter, the system correlates two monitoring targets and uses regression analysis to detect abnormalities, thereby reducing system complexity while maintaining detection capability
Solution Approach 2:
The patent introduces correlation data and regression line slope as intermediary elements between raw monitoring data and abnormality detection. These intermediaries simplify the detection process by transforming multiple parameters into a single analytical metric
2Measurement precision
If correlation analysis with regression calculation is performed, then measurement precision of abnormality detection is improved, but loss of time for data processing increases
Solution Approach 1:
The patent performs regression analysis only on selected correlation data points rather than continuously processing all possible data combinations. This partial action approach maintains detection precision while reducing unnecessary computational overhead and processing time
Data Source
AI summary
An abnormality detecting apparatus detects an abnormality of a semiconductor manufacturing apparatus, and includes: a data generator configured to generate correlation data based on a value of a first monitoring target and a value of a second monitoring target that are correlated with each other; a calculator configured to calculate a slop of a regression line of the correlation data based on the correlation data; and an abnormality determination device configured to determine an abnormality of the semiconductor manufacturing apparatus based on the slope of the regression line.