RFID-Based Sample Identification for Autosampler Error Reduction
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Solution Overview
Problem
Current autosampling systems face errors due to misidentification and misplacement of sample containers, leading to incorrect sample preparation and analysis protocols, which can result in inaccurate results and potential instrument damage, especially in industries with strict impurity tolerances like semiconductor manufacturing.
Innovation Solution
A system that automatically identifies unique samples using integrated informational systems, including a sample analysis information system, sample data manager, and sample logging manager, to apply specified analytical protocols based on sample identity, allowing for dynamic queuing and preparation of samples and standards for analysis without relying on a specific container arrangement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual sample identification and preparation methods are used, then flexibility in handling different sample types is maintained, but human error increases leading to misidentification and misplacement of sample containers
Solution Approach 1:
The system enables self-service through automatic sample identification using RFID tags and readers. The autosampler independently identifies sample containers, retrieves them from storage positions, and prepares them for analysis without human intervention, thereby eliminating misidentification errors while maintaining system simplicity through automated self-management
Solution Approach 2:
Manual mechanical operations of sample identification and handling are replaced by an automated system combining RFID electromagnetic field detection with mechanical autosampler operations. The RFID system substitutes manual visual identification, while the autosampler replaces manual sample retrieval and preparation, reducing human error without significantly increasing perceived system complexity
2Reliability
If sample containers are arranged in specific positions, then sample preparation protocols can be executed, but errors occur when samples are misplaced or identified incorrectly
Solution Approach 1:
The system transitions from static position-based sample identification to dynamic RFID-based identification. Sample containers can be placed in any storage position without fixed arrangement requirements, as the RFID reader dynamically identifies each sample's unique identifier and retrieves the correct preparation protocol, making the system adaptable to any container placement while ensuring accurate sample preparation
Solution Approach 2:
The RFID tag acts as an intermediary between the sample container and the autosampler system. Instead of relying on physical position or visual identification, the RFID tag carries sample identification information that the reader automatically detects, serving as a mediator that decouples sample placement requirements from identification accuracy, allowing flexible sample arrangement without compromising preparation reliability
3Adaptability or versatility
If multiple sample types with different protocols are processed, then analytical comprehensive is improved, but risk of instrument damage from incorrect protocols increases
Solution Approach 1:
The system implements feedback through RFID-based sample identification that automatically retrieves the correct preparation protocol from the control system. The protocol selection is feedback-driven based on the detected sample identifier, ensuring that only the appropriate protocol is executed for each sample type. This closed-loop feedback mechanism prevents incorrect protocol application that could damage the instrument while maintaining high adaptability to diverse sample types
Solution Approach 2:
The system performs preliminary action by pre-storing multiple sample preparation protocols in the control system, each associated with specific sample identifiers. Before processing any sample, the system preliminarily identifies the sample type via RFID and pre-selects the appropriate protocol, ensuring that the correct preparation method is ready and waiting, thereby preventing instrument damage from incorrect protocols while maintaining versatility across multiple sample types
Data Source
AI summary
Systems and methods for managing a sample preparation and analysis system based on detected unique sample identities and locations is described. A system embodiment includes, but is not limited to, a sample analysis information system communicatively connected with each of a sample data manager, a sample logging manager, and a sample preparation system, wherein the sample data manager stores on the sample analysis information system a sample type with a sample type protocol for execution by the sample preparation system, the sample logging manager assigns the sample type with a unique identifier positioned on a sample container, and the sample preparation system includes an identifier capture device to identify the unique identifier, access the sample type protocol from the sample analysis information system, and execute the sample type protocol responsive to a queue associated with a sample order assigned to the sample type via the sample data manager.