Experimental Protocol Parameter Management via Automatic Sample Tracking
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Solution Overview
Problem
Existing experimental protocols require manual updating of sample amounts in containers after each execution, reducing efficiency as users must update each sample individually, with no consideration for efficient content updates in previous configurations.
Innovation Solution
A method and system that utilize a specific application to set and update parameters based on sample amounts in containers, automatically executing and updating experimental protocols through a terminal device and controller, eliminating the need for manual updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual updating of sample amounts is performed after each experimental protocol execution, then accuracy of sample amount information is maintained, but efficiency of automatic execution decreases due to time-consuming individual updates
Solution Approach 1:
The system pre-calculates and stores the change in sample amount based on the experimental protocol configuration before execution. This preliminary action allows the system to automatically update sample amounts after execution without manual intervention, resolving the contradiction between maintaining accuracy and improving efficiency.
Solution Approach 2:
The system implements an automatic feedback mechanism where the change in sample amount calculated from the protocol configuration is fed back to update the container's sample amount information after execution. This closed-loop feedback eliminates manual updating while maintaining accuracy, simultaneously improving both precision and productivity.
2Loss of information
If manual updating of each sample amount is required after experimental protocol execution, then accurate tracking of sample consumption is achieved, but user workload increases and automation is reduced
Solution Approach 1:
The system performs self-service by automatically calculating the change in sample amount based on the experimental protocol configuration and updating the container information without user intervention. This self-updating mechanism maintains accurate tracking of sample consumption while eliminating manual workload, thereby improving both information accuracy and automation extent.
Solution Approach 2:
The system pre-configures the change in sample amount as part of the experimental protocol setup. This preliminary configuration enables automatic calculation and updating after execution, allowing the system to autonomously track sample consumption without requiring user actions, thus resolving the contradiction between information accuracy and automation level.
3Reliability
If the system stores and manages sample amount changes for each container, then accuracy of experimental data is improved, but system complexity increases
Solution Approach 1:
The system uses a universal data structure that stores both the absolute sample amount and the change in sample amount in a unified manner. This multi-functional approach allows the system to maintain accurate experimental data while avoiding the need for separate complex tracking mechanisms, thereby improving reliability without proportionally increasing system complexity.
Solution Approach 2:
The system pre-calculates and stores the change in sample amount as part of the protocol configuration. This preliminary action simplifies the data management structure by consolidating sample amount information in a single location that can be automatically updated, maintaining data accuracy while reducing the complexity of multiple separate tracking systems.
Data Source
AI summary
Efficiency of automatic execution of an experimental protocol is improved. A specific application executed in a terminal device sets a first parameter according to an amount of a sample contained in a specific container used in the experimental protocol. The specific application sets a second parameter according to a change in the amount of the sample in specific processing using the specific container in the experimental protocol. A controller automatically executes the experimental protocol based upon the first parameter and the second parameter. The specific application updates the first parameter based upon the second parameter.