Analysis Assistance Device Optimizing Measurement Quality Index
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Solution Overview
Problem
Existing analysis devices face challenges in optimizing analysis conditions due to variability in analysis results, which limits the ability to efficiently determine optimal settings for sample analysis.
Innovation Solution
An analysis assistance device that includes an estimator to predict the distribution of measurement quality index data using multiple analysis conditions and measurement data, a calculator to calculate measurement quality index data, and a comparison outputter to display and compare estimated and calculated data, providing users with valuable information for optimizing analysis conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If method scouting is performed to search for optimal analysis conditions, then analysis reliability is improved, but analysis time and complexity increase
Solution Approach 1:
The system performs preliminary estimation of measurement quality index distribution using a predictive model before actual analysis is conducted. This allows users to predict optimal analysis conditions in advance, reducing the time required for method scouting while maintaining analysis reliability.
Solution Approach 2:
The system creates a virtual model (copy) of the analysis process that can predict measurement quality outcomes without requiring actual physical analysis. This computational model allows multiple condition evaluations to be performed rapidly, reducing the time penalty associated with thorough method scouting.
2Measurement precision
If multiple analysis conditions are evaluated to optimize results, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system introduces an intermediary predictive model that evaluates multiple analysis conditions without requiring complex physical experimentation for each condition. This intermediary model simplifies the overall system complexity while enabling comprehensive evaluation of multiple parameters to achieve high measurement precision.
Solution Approach 2:
The system evaluates multiple analysis conditions by systematically varying parameters in a computational model rather than requiring physical reconfiguration for each condition. This approach maintains measurement precision through thorough parameter exploration while avoiding the complexity of physical system reconfiguration.
3Loss of information
If comprehensive analysis condition optimization is performed, then information quality is improved, but processing complexity increases
Solution Approach 1:
The system extracts the essential relationships between analysis conditions and measurement quality into a standalone predictive model. This extracted model provides comprehensive information about condition optimization without requiring the full complexity of the original analysis system, reducing processing complexity while maintaining information quality.
Data Source
AI summary
An analysis assistance device includes an estimator that estimates distribution of measurement quality index data using a plurality of analysis condition data to be provided to an analysis device and a plurality of measurement data obtained in the analysis device based on the plurality of analysis condition data, a calculator that calculates the measurement quality index data from the measurement data obtained from the analysis device, and a comparison outputter that compares and outputs for display the measurement quality index data estimated by the estimator and the measurement quality index data calculated by the calculator.