AI Blockchain System for 3D Printed Medical Device Traceability
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Solution Overview
Problem
Current regulations do not adequately address the life cycle management of 3D printed medical devices, particularly those manufactured in hospitals, leading to issues with traceability, ownership, and regulatory compliance due to their point-of-care production.
Innovation Solution
A processor-implemented method and system utilizing AI and blockchain technology to track materials and procedures in additive manufacturing, analyze design risks, identify potential hazards, and ensure compliance with regulations by auditing designs and updating smart contracts, while labeling devices with unique codes for regulatory purposes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If 3D printing technology is used to manufacture medical devices at point of care, then flexibility and customization are improved, but traceability and regulatory compliance deteriorate
Solution Approach 1:
The system performs preliminary actions by pre-defining regulatory parameters, material specifications, and procedural requirements before the 3D printing process begins. Smart contracts encode these requirements in advance, ensuring that customization occurs within pre-established regulatory frameworks, thus maintaining traceability while enabling flexibility.
Solution Approach 2:
The system implements continuous feedback loops where each step of the 3D printing process (material selection, design validation, manufacturing parameters) is monitored and recorded. This feedback mechanism ensures that deviations from regulatory requirements are immediately detected and corrected, maintaining traceability throughout the customization process.
2Reliability
If comprehensive tracking and auditing systems are implemented, then regulatory compliance is improved, but system complexity increases
Solution Approach 1:
The blockchain-based platform serves multiple functions simultaneously: it tracks materials, validates designs, monitors manufacturing processes, stores regulatory parameters, and generates compliance certificates. This multi-functionality consolidates what would otherwise be separate complex systems into a single unified platform, improving compliance while managing overall system complexity.
Solution Approach 2:
The system employs automated smart contracts that self-execute compliance checks and validations without requiring manual intervention. The automated auditing process and self-updating regulatory databases reduce the need for complex manual tracking systems, simplifying the overall system architecture while maintaining comprehensive compliance monitoring.
3Measurement precision
If AI models are trained with extensive material datasets, then hazard identification accuracy is improved, but data processing time increases
Solution Approach 1:
The AI model is trained in advance with comprehensive material datasets, hazard scenarios, and regulatory requirements before actual 3D printing operations begin. This preliminary training enables the model to rapidly assess hazards during manufacturing without requiring real-time data processing, thus achieving high accuracy without significant time loss during production.
Solution Approach 2:
The system uses a two-stage approach where the AI model first performs a rapid preliminary hazard assessment using key parameters, then applies more detailed analysis only when potential hazards are detected. This partial application of extensive analysis reduces overall processing time while maintaining high accuracy for critical hazard identification.
Data Source
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AI summary
This disclosure relates to a system and method for custom made medical devices life cycle management. the life cycle management of the medical devices include tracking of material and procedure to be used in additive manufacturing of the medical device and analyzing design risk as per the raw material and the design specification. Further, it includes to identify potential hazards based upon the materials, their interactions and effect on process to be followed. An artificial intelligence (AI) enabled model is trained with one or more sample datasets pertaining to a plurality of materials to be used in the additive manufacturing to audit design, to determine materials to be used, and to generate a unique code to be used to label the manufactured medical device. A smart contract of blockchain is configured to record received input and update with new points for regulatory compliance.