Working Wire Coating Control for Uniform Continuous Sensor Dipping
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Solution Overview
Problem
The high cost and inefficiency of manufacturing working wires for continuous glucose monitors, which are crucial for accurate glucose level monitoring in diabetes patients, due to the time-consuming and costly process of producing disposable sensors, limit their accessibility and reliability.
Innovation Solution
An automated system measures the dimensions of working wires during the dipping process and adjusts parameters in real-time to optimize coating thickness, reducing the number of dips required and improving accuracy, using a controller that communicates with an industrial robot to manage dipping parameters such as viscosity, temperature, and withdrawal speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional manual dipping processes are used to manufacture working wires, then manufacturing precision can be maintained through operator skill, but productivity is low and production costs are high due to time-consuming processes
Solution Approach 1:
The system employs real-time feedback control where coating thickness is continuously monitored during the dipping process and the withdrawal speed is dynamically adjusted to maintain uniform coating thickness, resolving the contradiction between high-speed automated dipping and coating precision
Solution Approach 2:
The withdrawal speed is made dynamic rather than static, allowing the system to adapt the dipping parameters in real-time based on coating thickness measurements, enabling both high productivity and manufacturing precision
2Manufacturing precision
If multiple dipping iterations are performed to achieve desired coating thickness, then manufacturing precision improves, but loss of time increases and productivity decreases
Solution Approach 1:
Real-time thickness measurement and feedback control allow the system to achieve the desired coating thickness in fewer dipping iterations by adjusting parameters between dips, reducing total process time while maintaining precision
Solution Approach 2:
The system performs preliminary measurements and adjustments before completing the dipping process, allowing optimization of subsequent dipping iterations to minimize the number of passes required while achieving target thickness accuracy
3Manufacturing precision
If automated measurement systems are implemented to monitor coating thickness in real-time, then manufacturing precision improves, but device complexity increases
Solution Approach 1:
The system replaces complex mechanical measurement and adjustment mechanisms with automated optical or electromagnetic measurement systems controlled by software, reducing mechanical complexity while improving measurement accuracy and enabling real-time feedback
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 production costs, increases efficiency, and enhances the accuracy of working wires, making continuous glucose monitoring more accessible and reliable for diabetes patients.
Implementation Method 1
A plurality of diameters is measured along a length of at least two coated wires of the plurality of wires in the fixture, using an automated measurement system
Implementation Method 2
dipping the plurality of wires into a coating solution according to parameters for a dipping process
Data Source
AI summary
Methods for coating a working wire for a continuous biological sensor include providing a plurality of wires in a fixture and dipping the plurality of wires into a coating solution according to parameters for a dipping process. A plurality of diameters is measured along a length of at least two coated wires of the plurality of wires in the fixture, using an automated measurement system, as in an in-line process. A controller that is in communication with the automated measurement system determines a thickness difference, the thickness difference being a difference between a thickness setpoint and an aggregate criteria for the plurality of diameters. The controller calculates adjusted parameters for the dipping process based on the thickness difference.