RFID Syringe Nest Localization Using ML Read Parameters
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing mass reading methods for RFID-tagged syringes in nests fail to accurately determine the exact position of each syringe within the nest, impacting processing efficiency during filling operations.
Innovation Solution
A system utilizing a conveyor, RFID antennas, and a machine learning model to analyze read-related parameters and tag sensitivity of RFID tags, enabling precise localization of syringes within a nest by determining their column and seat positions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If mass reading method is used to read RFID tags of syringes in nest, then reading efficiency is improved, but location precision of each syringe deteriorates
Solution Approach 1:
The patent segments the mass reading process into individual syringe-level readings by positioning the RFID reader to read syringes one at a time as they pass through the reading zone on the conveyor, while still maintaining high throughput. This allows precise location identification (which chimney/seat each syringe occupies) without sacrificing overall reading efficiency.
2Reliability
If RFID tags are integrated into syringes for traceability, then traceability capability is improved, but device complexity deteriorates
Solution Approach 1:
The RFID tag serves multiple functions: it provides unique identification for traceability, enables location identification within the nest through read parameter analysis, and facilitates automated tracking throughout the manufacturing process. This multi-functionality reduces the need for separate tracking systems, ultimately simplifying the overall system despite the added RFID component.
3Productivity
If exact position of each syringe is determined, then processing efficiency is improved, but system complexity deteriorates
Solution Approach 1:
The patent replaces complex mechanical positioning systems with an RFID-based detection system. Instead of using mechanical sensors or cameras to locate each syringe, the system uses RFID read parameters (signal strength, phase, etc.) to determine which chimney/seat each syringe occupies, significantly reducing system complexity while maintaining precise location identification.
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
Accurately registers the location of each RFID-tagged syringe within a nest, enhancing processing efficiency and facilitating controlled filling operations.
Implementation Method 1
a RFID reader operably connected with the one or more RFID antennas and configured to perform a mass reading of the device RFID tags and a reading of the nest RFID tag
Data Source
Figure 1A
Figure 1B
Figure 1C
AI summary
Provided herein is a system for localizing RFID-tagged medical injection devices in a nest. The system includes a conveyor that conveys nests along a conveying path, each of the nests retaining RFID-tagged medical injection devices. RFID coupling elements and a RFID reader are positioned at a reading location along the conveying path, to read the RFID-tagged medical injection devices via a mass reading and to read the RFID-tagged nest when passing the reading location, including reading identifiers associated with the devices and the nest, as well as read-related parameters of the devices. A ML model receives a model input from the mass reading comprising the UDIs and read-related parameters of the device RFID tags and determines a location of each of the RFID-tagged medical injection devices within the nest based on analysis of the read-related parameters by the ML model.