Vehicle Component Telematics for Predictive Maintenance Timing
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Solution Overview
Problem
Current fleet management systems lack reliable methods to predict component failures in vehicles, leading to unnecessary replacements and increased costs due to the unreliability of manufacturer estimates and the variability of operating conditions across different vehicles.
Innovation Solution
A telematics-based system that monitors and analyzes operational data from vehicle components in real-time, using statistical methods to identify predictive indicators of component status, allowing for timely maintenance and replacement decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manufacturer's recommended maintenance schedule based on running total of mileage or operational time is used, then maintenance can be performed periodically, but the predictions are limited and inconclusive and cannot accurately predict component failure
Solution Approach 1:
The system transforms the maintenance approach by changing from fixed intervals (mileage/time) to dynamic parameter monitoring. It monitors multiple operational parameters simultaneously (temperature, pressure, vibration, operational cycles) and uses statistical analysis to determine when components are actually approaching failure, rather than following predetermined schedules.
Solution Approach 2:
The patent replaces the mechanical counting of mileage or operational time with electronic sensor-based monitoring and statistical analysis systems. Telematics devices collect data, and statistical models process this data to predict failure, substituting simple mechanical counters with sophisticated electronic measurement and analysis systems.
2Measurement precision
If simple comparison of current value with previous value is used, then the method is simple to implement, but it cannot accurately predict component failure
Solution Approach 1:
The system segments the analysis by dividing operational data into distinct phases or states (normal operation, degradation phase, critical phase). It applies different statistical methods to different segments of the component's life cycle, allowing for more accurate prediction while maintaining manageable system complexity through structured data organization.
Solution Approach 2:
The patent creates a universal predictive maintenance system that can be applied to multiple different component types across various vehicles. The same statistical framework and telematics infrastructure serve multiple functions: monitoring different parameters, predicting failures of various components, and providing maintenance recommendations across an entire fleet, reducing overall system complexity through standardization.
3Adaptability or versatility
If Mean Time Between Failure engineering data is used to predict elapsed time between failures, then predictions can be made based on historical data, but the predictions do not account for variability in operating conditions across different vehicles
Solution Approach 1:
The system transitions from static MTBF values to dynamic, real-time prediction. It continuously monitors current operational conditions and adjusts failure predictions dynamically based on actual vehicle usage patterns, environmental conditions, and component degradation rates, making the system adaptable to varying operating conditions while improving prediction reliability.
Solution Approach 2:
The patent implements feedback loops where actual component performance data and failure information are fed back into the statistical models. This allows the system to learn from real-world outcomes and continuously refine its predictions, accounting for variability in operating conditions across different vehicles and improving overall prediction reliability through iterative optimization.
Data Source
AI summary
Apparatus, device, methods and system relating to a vehicular telemetry environment for monitoring vehicle components and providing indications towards the condition of the vehicle components and providing optimal indications towards replacement or maintenance of vehicle components before vehicle component failure.