Analytical Instrumentation Dynamic Parameter Adjustment
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Solution Overview
Problem
Current analytical instrumentation, such as mass spectrometry systems, lack the ability to dynamically modify analytical component parameters during analysis, requiring manual redefinition and reconfiguration of parameters for acquiring additional data sets, which is inefficient and limits continuous monitoring capabilities.
Innovation Solution
Incorporating processing and control components with processing circuitry and storage devices that allow for the acquisition of data sets using initial parameter sets and dynamically modifying these parameters to prepare new sets, enabling continuous adjustment and optimization of analysis component configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual redefinition and reconfiguration of parameters is performed to acquire additional data sets, then analysis flexibility is improved, but analysis time and operational efficiency deteriorate
Solution Approach 1:
Multiple analysis parameter sets are pre-configured and stored in the system memory before analysis begins. When a data set is acquired, the system automatically retrieves and applies the corresponding pre-defined parameter set for subsequent analysis, eliminating the need for manual reconfiguration and enabling continuous automated analysis.
Solution Approach 2:
The system automatically processes acquired data sets and uses the results to trigger retrieval and application of appropriate analysis parameter sets. This closed-loop feedback mechanism enables the system to adaptively adjust analysis parameters based on actual data characteristics without manual intervention, maintaining flexibility while reducing time loss.
2Adaptability or versatility
If multiple analysis parameter sets are manually configured and downloaded, then analytical versatility is improved, but device complexity and operational burden increase
Solution Approach 1:
The system merges the functions of multiple parameter configuration operations into a single automated process. Multiple analysis parameter sets are integrated into one unified memory storage, and the system automatically manages their selection and application based on data set characteristics, reducing operational complexity while maintaining analytical versatility.
Solution Approach 2:
The system performs self-service by automatically selecting and applying appropriate analysis parameter sets from its internal storage based on the characteristics of acquired data. This eliminates the need for operator intervention in parameter management, reducing operational burden while preserving the ability to handle diverse analytical requirements.
3Productivity
If continuous monitoring is implemented without dynamic parameter modification, then system simplicity is maintained, but monitoring effectiveness and data quality deteriorate
Solution Approach 1:
Different analysis parameter sets are pre-configured for different monitoring scenarios and data characteristics. The system automatically selects the appropriate pre-configured parameter set based on the current data being analyzed, enabling effective continuous monitoring without requiring complex real-time parameter adjustment mechanisms.
Solution Approach 2:
The system implements dynamic parameter modification by automatically switching between different pre-configured analysis parameter sets during continuous monitoring operations. This allows the system to adapt to varying data characteristics and monitoring requirements in real-time, significantly improving monitoring effectiveness while keeping the underlying system architecture relatively simple.
Data Source
AI summary
A sample analysis apparatus (10) includes processing circuitry (22) coupled to a data set device (20) and a storage device (24) to acquire one data set from an analysis component (14) according to one analysis parameter set and to prepare another analysis parameter set using another previously acquired data set.