X-ray Tube Assembly Predictive Maintenance System
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Solution Overview
Problem
Unplanned shutdowns of radiological imaging systems due to X-ray tube failures disrupt healthcare services and revenue, with existing prediction methods lacking accuracy and lead time for maintenance scheduling.
Innovation Solution
A system and method that predict the remaining lifespan of X-ray tube assemblies by acquiring age and operating parameters, including event codes associated with abnormal conditions, to adjust survivability probabilities and automate maintenance scheduling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing prediction methods are used, then maintenance can be scheduled, but prediction accuracy and lead time are insufficient
Solution Approach 1:
The system performs preliminary actions by continuously monitoring operating parameters and event codes before actual failure occurs. It calculates remaining useful life and predicts failure timestamps in advance, enabling maintenance to be scheduled proactively rather than reactively, thus providing sufficient lead time while maintaining high prediction accuracy
Solution Approach 2:
The system implements feedback mechanisms by continuously acquiring operating parameters and event codes from the imaging system, comparing them against historical data and failure patterns, and updating predictions in real-time. This closed-loop feedback enables the system to adapt to changing conditions and maintain high prediction accuracy while providing timely warnings
2Productivity
If X-ray tube failure is not predicted, then system operation continues, but unplanned shutdowns disrupt healthcare services and revenue
Solution Approach 1:
The system schedules maintenance in advance based on predicted failure timestamps, ensuring that the X-ray tube is replaced before actual failure occurs. This preliminary action prevents unplanned shutdowns and maintains both system reliability and healthcare service productivity
Solution Approach 2:
The system takes preliminary anti-action by predicting and preventing failure before it occurs. Through continuous monitoring and prediction, it counteracts the potential harmful effect of tube failure on system availability and healthcare service delivery, maintaining both reliability and productivity
Data Source
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AI summary
A system (100) and method (300) to predict a failure of an imaging system (105) that includes a radiation source (110) having an x-ray tube assembly (115) is provided. The system (100) includes a storage medium (155) having a plurality of programmable storage instructions to instruct a processor (150) to perform the steps of acquiring an age of the x-ray tube assembly (115), calculating a baseline probability of a survivability of the tube assembly (115) for a remaining time period dependent on the age of the tube assembly (115), acquiring measurement of at least one operating parameter of the x-ray tube assembly (115), and automatically changing the baseline probability of a survivability of the imaging system (105) for the remaining time period in response to the measurement of the at least one operating parameter of the x-ray tube assembly (115).