Autonomous Particle Processing with Self-Calibration and Feedback
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Solution Overview
Problem
Current particle processing systems require significant human intervention for setup, calibration, operation, and maintenance, which can be time-consuming and prone to errors, and do not allow for autonomous operation.
Innovation Solution
A particle processing system that includes a detection region, a particle delivery assembly, a charge device controlled by a controller, a radiation source assembly, an imaging assembly, and a processor programmed to perform various sensing and processing functions autonomously, minimizing human intervention by automating setup, calibration, analysis, sorting, and monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If particle processing systems are operated with human intervention for setup, calibration, and operation, then operational flexibility and error correction are improved, but time consumption and operator dependency increase
Solution Approach 1:
The system performs self-calibration by automatically adjusting operational parameters based on real-time sensor feedback without requiring manual operator intervention. The processor autonomously analyzes particle flow characteristics and modifies calibration settings, eliminating time-consuming manual setup while maintaining measurement accuracy.
Solution Approach 2:
Sensors continuously monitor particle flow parameters and feed this information back to the processor, which automatically adjusts operational parameters to maintain optimal performance. This closed-loop feedback system reduces errors by detecting and correcting deviations in real-time without human intervention.
2Productivity
If particle processing systems are automated to reduce human intervention, then operational efficiency and continuity are improved, but system complexity increases
Solution Approach 1:
The processor serves multiple functions simultaneously: it controls particle delivery, analyzes sensor data, adjusts calibration parameters, and monitors system performance. This multi-functionality consolidates what would otherwise require separate automated subsystems, maintaining high productivity while limiting the increase in overall system complexity.
Solution Approach 2:
Manual mechanical calibration adjustments are replaced with electronic sensor feedback and digital parameter modification. The system uses electronic sensing and computational processing instead of mechanical calibration mechanisms, achieving automation efficiency while reducing the complexity of mechanical moving parts.
3Adaptability or versatility
If manual calibration and setup procedures are used, then system adaptability to different conditions is improved, but operator skill requirements and time consumption increase
Solution Approach 1:
The system automatically adapts to different particle types and flow conditions through self-calibration. Sensors detect particle characteristics and the processor autonomously adjusts operational parameters, eliminating the need for operators to manually adapt calibration settings for different sample types while maintaining full adaptability.
Solution Approach 2:
The system dynamically modifies operational parameters based on real-time sensor measurements of particle flow characteristics. By automatically changing parameters such as flow rate, detection sensitivity, and sorting thresholds, the system maintains adaptability to varying conditions without requiring skilled operators to manually reconfigure settings.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system significantly reduces the burden of human intervention, improving run performance and operational efficiency by enabling autonomous operation, reducing errors, and allowing for continuous operation without the need for skilled operators.
Implementation Method 1
an imaging assembly (102) including an optical system (160) and a sensing element (162) for imaging the droplet
Implementation Method 2
a charge device controlled by a controller (158) to selectively apply a charge to a droplet in a stream of droplets
Data Source
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AI summary
The present disclosure provides improved particle processing (e.g., cytometry and/or cell purification) systems and methods that can operate in an autonomous fashion. More particularly, the present disclosure provides for assemblies, systems and methods for analyzing, sorting, and/or processing (e.g., purifying, measuring, isolating, detecting and/or enriching) particles (e.g., cells, microscopic particles, etc.) where human intervention is not required and/or is minimized. The systems, assemblies and methods of the present disclosure advantageously improve run performance of particle processing systems (e.g., cell purification systems, cytometers) by significantly reducing and/or substantially eliminating the burden of operation for human intervention by automating numerous functions, features and/or steps of the disclosed systems and methods.