Analytical Sample Container Classification via Pre-Entry Identifier Checks
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Solution Overview
Problem
Existing automated systems for identifying analytical sample containers in in vitro diagnostic (IVD) laboratories are prone to errors due to damaged or incorrectly applied visual identifiers, leading to inefficiencies and potential system downtime, especially for urgent tests.
Innovation Solution
A computer-implemented method and system that uses an optical identifier reader and/or camera to assess the ability of analytical system apparatuses to read visual identifiers, enabling proactive detection and correction of defects before sample containers enter the system, utilizing a data processing agent to classify and output messages on identifier quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated means are used to identify sample containers using barcodes or QR codes, then identification speed and throughput are improved, but errors occur due to damaged or incorrectly applied visual identifiers requiring manual intervention
Solution Approach 1:
The patent applies preliminary action by checking the visual identifier quality before the sample container enters the analytical system. The system proactively identifies potential reading failures by comparing the visual identifier characteristics against known failure patterns, and routes problematic samples to alternative apparatuses before the reading failure occurs, thus preventing system downtime and manual intervention.
Solution Approach 2:
The patent implements dynamics by creating a dynamic routing system that adapts to the real-time quality of visual identifiers. The system continuously monitors visual identifier characteristics and dynamically adjusts the routing of sample containers to appropriate apparatuses based on their reading capabilities, rather than using a static assignment approach.
2Reliability
If manual inspection and rerouting of unidentifiable sample containers is performed, then identification accuracy is improved, but system downtime increases and productivity decreases
Solution Approach 1:
The system performs preliminary classification of visual identifier quality before sample containers enter the analytical system. By proactively identifying potential reading failures and pre-routing samples to appropriate apparatuses, the system eliminates the need for manual inspection and rerouting during operation, thus maintaining both high accuracy and productivity.
Solution Approach 2:
The system implements self-service by automatically routing sample containers to appropriate apparatuses based on visual identifier quality assessment. The system independently identifies and resolves potential identification issues without requiring manual intervention, thereby maintaining continuous operation and high throughput while ensuring accurate identification.
3Reliability
If visual identifiers are checked at multiple points in the analytical system, then identification reliability is improved, but device complexity and processing time increase
Solution Approach 1:
The patent applies preliminary action by performing visual identifier quality assessment at the entry point to the analytical system, before samples are distributed to various apparatuses. This single preliminary check is sufficient to identify potential reading failures and route samples appropriately, eliminating the need for multiple redundant checks throughout the system while maintaining high reliability.
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
This approach reduces system downtime and increases throughput by allowing for proactive correction of visual identifier issues, ensuring that urgent tests are less likely to be delayed and minimizing the need for manual intervention.
Implementation Method 1
the at least one apparatus comprises an optical identifier reader and/or camera
Data Source
AI summary
A computer implemented method for analytical sample container classification, wherein the method comprises obtaining a digital representation of a visual identifier associated with a sample container; identifying at least one apparatus comprised within an analytical system, wherein the analytical system is intended to perform at least one analytical test using the sample container, wherein the at least one apparatus comprises an optical identifier reader; classifying the sample container associated with the visual identifier by characterizing the ability of the optical identifier reader of the at least one apparatus comprised in the analytical system to decode the visual identifier associated with the sample container, to thereby generate a corresponding classification result characterizing the sample container associated with the visual identifier; and outputting a message defining the classification result.