Microplate Dispensing Control Using Measured Concentration Data
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing dispensing systems require users to manually select pipettes, dispensing positions, and determine liquid parameters, increasing the user's workload.
Innovation Solution
A dispensing system and method that automates the selection of pipettes and dispensing positions, and calculates dispensing amounts based on measured data, reducing user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the user manually selects pipettes, dispensing positions, and determines liquid parameters, then the system provides full control and flexibility, but the user's workload increases
Solution Approach 1:
The system automatically selects appropriate pipettes based on liquid volume requirements, determines optimal dispensing positions using vision systems, and calculates dispensing parameters based on measured liquid properties. This self-service capability eliminates manual user input for these parameters, directly reducing user workload while maintaining operational flexibility through automated decision-making algorithms
Solution Approach 2:
The system performs preliminary actions by pre-configuring pipette selection criteria, pre-processing vision data to identify dispensing positions, and pre-calculating dispensing parameters before actual dispensing operations begin. This preliminary automation prepares all necessary parameters in advance, reducing real-time user intervention and streamlining the dispensing workflow
2Productivity
If the system automates pipette selection and dispensing position determination, then user workload is reduced, but the device complexity increases
Solution Approach 1:
The system employs a multi-functional architecture where a single automated control unit handles pipette selection, vision-based position determination, parameter calculation, and dispensing control. This universal controller integrates multiple functions that would otherwise require separate systems, achieving high dispensing efficiency while managing complexity through centralized intelligent control rather than multiple specialized components
Solution Approach 2:
The system replaces manual mechanical operations with automated electronic control. Vision systems substitute for manual visual inspection, automated algorithms replace manual calculation of dispensing parameters, and electronic control systems replace manual pipette handling. This substitution of mechanical and manual processes with electronic automation increases productivity while consolidating complexity into software and control systems rather than mechanical complexity
3Measurement precision
If the system performs automated calculations based on measured data, then accuracy is improved, but the processing time increases
Solution Approach 1:
The system performs measurements and calculations in continuous operation rather than discrete steps. The vision system continuously tracks liquid properties, and the control algorithm continuously adjusts dispensing parameters based on real-time feedback. This continuous measurement and calculation process maintains high accuracy without interruption, eliminating the need for repeated measurement-calculation cycles that would increase processing time
Data Source
Figure 1
Figure 2~3
Figure 4
AI summary
The dispensing system 1 includes a robot 2, a host controller 4 including a measured data acquisition part 41, and a robot controller 3 including a dispensing operation execution part 30. The robot 2 performs a dispensing work related to a stock solution 15 stored in each of a plurality of wells 12 of a microplate 10. The measured data acquisition part 41 acquires measured data of concentration of the stock solution 15. The dispensing operation execution part 30 controls the robot 2 to perform a dispensing operation on a basis of the measured data based on a dispensing command from the host controller 4.