Medical Device Failure Prediction via Sensor Simulation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Medical-technical devices lack effective monitoring and predictive maintenance for wear-prone components, leading to unexpected failures and potential safety risks, as existing systems do not adequately consider indication-dependent wear or provide reliable failure prognosis.
Innovation Solution
A sensor system that senses operating parameters of medical-technical devices, simulates their behavior using known wear properties, and calculates the likelihood of failure, displaying the result in terms of remaining usable life or cycles, and transmitting this data to a replacement device to enable preventive maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If preventive maintenance is based on precautionary replacement of critical components during periodical maintenance, then device reliability is improved, but loss of time and productivity increase due to unnecessary replacements
Solution Approach 1:
The system performs preliminary simulation of component wear and failure likelihood before actual failure occurs. By using sensor data and simulation models to predict when components will fail, maintenance can be scheduled precisely when needed rather than replacing components preemptively, thus reducing unnecessary downtime while maintaining reliability
Solution Approach 2:
The system continuously monitors component status through sensors and provides feedback on actual wear and failure likelihood. This feedback loop allows dynamic adjustment of maintenance schedules based on real-time component condition rather than fixed schedules, optimizing the balance between reliability and minimizing downtime
2Ease of operation
If component replacement is performed without considering indication-dependent wear, then ease of operation is improved, but measurement precision and reliability of failure prognosis deteriorate
Solution Approach 1:
The system recognizes that different indications (medical applications) impose different stress patterns on components, leading to different wear rates. By tailoring the simulation model to the specific indication being performed, the system achieves accurate failure predictions for each local usage condition rather than applying a generic replacement schedule
Solution Approach 2:
The simulation model incorporates indication-dependent parameters such as operating duration, load intensity, and operational patterns specific to different medical procedures. By adjusting these parameters based on the actual indication, the system maintains high prediction accuracy while keeping the interface simple for operators
3Reliability
If sensor-based monitoring of all failure-relevant conditions is implemented, then reliability and measurement precision are improved, but device complexity increases
Solution Approach 1:
The system uses a multi-functional simulation model that can assess the failure likelihood of different component types (pump, motor, valves, etc.) using a unified approach. This universal model consolidates what would otherwise require multiple separate monitoring systems, reducing overall complexity while maintaining comprehensive reliability monitoring across all components
Solution Approach 2:
The simulation module acts as an intermediary that processes data from multiple sensors and translates it into meaningful failure predictions. Rather than requiring direct complex interactions between multiple sensors and control systems, the simulation model mediates by integrating sensor data and providing simplified reliability assessments
4Reliability
If precautionary replacement of components is performed frequently, then reliability is improved, but loss of substance and waste increase
Solution Approach 1:
The system performs preliminary assessment of actual component wear through simulation before replacement is performed. By accurately predicting which components will fail and when, the system enables replacement only when necessary rather than frequent preemptive replacement, thus reducing component waste while maintaining device availability
Data Source
AI summary
Subject matter of the invention is a medical-technical system comprising a sensor system for directly or indirectly sensing all conditions relevant to a failure of the subassemblies of the medical-technical system, and a simulation module, which simulates, based on the sensor data and selected applications of the medical-technical system, the actual operating parameter values, the history of use, and the effects caused by the indication with the aid of the known wear properties of the components, the application-dependent stability of the components in the medical-technical system, and outputs it in a complete or simplified form or as instructions for repair.