Injection System Predictive Maintenance for Failure and Misuse Detection
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Solution Overview
Problem
Conventional injection systems lack a mechanism for predicting operation failures and misuses, leading to potential downtime, improper functioning, and delayed or improper medical procedures.
Innovation Solution
A computer-implemented method and system for predictive maintenance that receives operation data from injection systems, determines prediction scores for potential failures or misuses, and provides maintenance data to prevent such issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional injection systems operate without predictive maintenance mechanisms, then device complexity is reduced, but reliability deteriorates due to unexpected failures and downtime
Solution Approach 1:
The system performs preliminary maintenance actions by predicting potential failures before they occur. The predictive maintenance module analyzes operation data to identify patterns indicating future failures, allowing maintenance to be scheduled proactively rather than reactively, thus improving reliability without requiring complex real-time intervention mechanisms
Solution Approach 2:
The system implements feedback loops where operation data is continuously collected, analyzed, and used to update prediction models. Maintenance predictions are fed back into the system to adjust monitoring parameters and improve future predictions, creating a self-improving maintenance system that enhances reliability while managing complexity through iterative optimization
2Productivity
If predictive maintenance is implemented to reduce downtime, then productivity improves, but device complexity increases due to additional sensors and data processing requirements
Solution Approach 1:
The system uses multi-functional operation data that serves both real-time control purposes and predictive maintenance analysis. The same sensors and data collection infrastructure used for basic injection system operation are leveraged for predictive analytics, eliminating the need for separate dedicated monitoring systems and reducing overall device complexity while maintaining high productivity
Solution Approach 2:
The predictive maintenance system performs self-diagnosis and self-prediction by analyzing its own operation data. The system automatically identifies patterns indicating future failures and schedules its own maintenance without external intervention, reducing the need for complex external monitoring infrastructure while improving productivity through minimized downtime
3Reliability
If operation data is collected and analyzed for failure prediction, then reliability improves, but loss of time increases due to data processing requirements
Solution Approach 1:
The system performs preliminary data processing and pattern recognition during normal operation to prepare prediction models in advance. By pre-processing operation data and identifying potential failure patterns before critical events occur, the system minimizes real-time data processing requirements while maintaining high prediction accuracy, thus reducing time loss without compromising reliability
Data Source
AI summary
A method, system, and computer program product for predictive maintenance. A method may include receiving operation data associated with one or more injection systems, wherein the operation data includes one or more operation parameters associated with one or more operations of the one or more injection systems; determining one or more prediction scores for the one or more injection systems based on the operation data, wherein the one or more prediction scores include one or more predictions of one or more operation failures or misuses for the one or more injection systems; and providing maintenance data associated with the one or more operation failures or misuses, wherein the maintenance data is based on the one or more prediction scores.