Segmented Sensor Log Analysis for Substrate Tool Differences
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Solution Overview
Problem
Existing methods for analyzing inter-apparatus differences in substrate processing apparatuses require manual expert intervention to narrow down sensors, are limited to specific sensors, and lack comprehensive analysis of the entire sensor group, making it difficult to identify defects and inefficiencies.
Innovation Solution
An analysis device that divides log data from multiple substrate processing apparatuses into segments and analyzes the entire sensor group comprehensively, allowing visualization and display of inter-apparatus differences, reducing the need for manual sensor selection and enabling efficient identification of defective parts or sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual expert intervention is used to narrow down sensors for analysis, then analysis depth for specific sensors is improved, but analysis coverage of the entire sensor group deteriorates and expert workload increases
Solution Approach 1:
The patent segments the sensor group into multiple categories (temperature sensors, pressure sensors, flow rate sensors, etc.) and performs automated analysis on each category. This segmentation enables comprehensive coverage of all sensors while maintaining detailed analysis depth through systematic categorization and automated processing of each segment.
Solution Approach 2:
The system performs self-service automated analysis by automatically collecting sensor data, categorizing sensors, analyzing inter-apparatus differences, and generating reports without requiring manual expert intervention. This self-service mechanism eliminates the trade-off by automating what previously required expert selection while covering the entire sensor group.
2Adaptability or versatility
If comprehensive analysis of the entire sensor group is performed, then analysis coverage is improved, but data processing complexity and time consumption increase
Solution Approach 1:
By segmenting sensors into categories and processing each category separately with appropriate analysis methods, the system reduces overall data processing complexity. Each sensor category can be analyzed using optimized algorithms specific to that type, rather than applying a single complex method to all sensors.
Solution Approach 2:
The patent implements a universal automated analysis framework that handles multiple sensor types through a common processing structure. This multi-functional system provides standardized data collection, categorization, and analysis procedures that work across all sensor types, reducing complexity through uniformity while maintaining comprehensive coverage.
3Ease of operation
If automated analysis of the entire sensor group is implemented, then expert workload is reduced, but measurement precision and defect identification accuracy may deteriorate
Solution Approach 1:
The system performs self-service automated analysis that eliminates the need for manual sensor selection while maintaining high defect identification accuracy through systematic algorithms. The automated process objectively analyzes all sensors without human bias, and the comprehensive coverage ensures that defects are not missed due to incomplete sensor selection.
Solution Approach 2:
The system incorporates feedback mechanisms where analysis results are used to refine and improve the automated analysis process. By continuously learning from analysis outcomes and inter-apparatus difference patterns, the system enhances defect identification accuracy over time while maintaining automated operation and reducing expert workload.
Data Source
AI summary
An analysis device includes a processor; and a memory storing program instructions that cause the processor to divide log data of each of sensors of sensor groups for detecting states of each of a plurality of substrate processing apparatuses into segments and store the log data divided for each of the segments in a data storage unit for each of the sensors; perform an analysis on an inter-apparatus difference between the plurality of substrate processing apparatuses by analyzing each of the plurality of substrate processing apparatuses based on the log data divided for each of the segments stored in the data storage unit; and display a result of the analysis.