Aircraft Maintenance Induction Using Structural Degradation Prediction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current maintenance induction methods for aircraft are not optimal as they do not account for varying flight conditions and stress levels, making it difficult to determine which aircraft sections are degraded and requiring maintenance, leading to increased costs and reduced availability.
Innovation Solution
A data-driven approach using onboard sensors to measure fatigue metrics, regression models to predict structural degradation, and prioritize maintenance based on aircraft usage and health conditions, routing aircraft to facilities with the necessary capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional maintenance induction methods are used, then maintenance can be performed on aircraft, but it does not account for varying flight conditions and stress levels, making it difficult to determine which aircraft sections are degraded
Solution Approach 1:
The patent replaces traditional mechanical inspection methods with sensor-based measurement systems that use strain gauges, accelerometers, and other sensors to detect structural degradation. This substitution enables precise measurement of stress levels and flight conditions, resolving the contradiction between detection precision and information loss by providing quantitative data on aircraft structural health.
Solution Approach 2:
The patent introduces data management systems and algorithms as intermediaries between the sensors and maintenance decision-making processes. These intermediaries process raw sensor data, correlate flight conditions with stress levels, and generate actionable insights about structural degradation, thereby preventing information loss and improving detection precision simultaneously.
2Productivity
If maintenance is performed without precise structural degradation prediction, then aircraft can be maintained, but it leads to increased costs and reduced availability
Solution Approach 1:
The patent implements preliminary action by continuously monitoring structural health parameters and predicting future degradation trends before actual degradation occurs. This allows maintenance to be scheduled proactively based on predicted degradation patterns rather than reactively after problems arise, improving aircraft availability while optimizing maintenance cost efficiency through targeted interventions.
Solution Approach 2:
The patent applies dynamics by transitioning from static, schedule-based maintenance to dynamic, condition-based maintenance. The system continuously adapts maintenance recommendations based on real-time sensor data, flight conditions, and predicted degradation patterns, allowing aircraft to remain in service longer when conditions permit while ensuring maintenance is performed precisely when needed, thereby improving both availability and cost efficiency.
Data Source
AI summary
An apparatus for predicting structural degradation and performing maintenance induction for a plurality of in-service aircraft is provided. The apparatus identifies maintenance requirements for the plurality of in-service aircraft and receives fatigue metric values on historical usage and structural health condition of the plurality of in-service aircraft. The apparatus predicts levels of structural degradation to the plurality of in-service aircraft based on the fatigue metric values and assigns maintenance priorities to the plurality of in-service aircraft based on the levels of structural degradation. The apparatus generates an instruction to route an aircraft of the plurality of in-service aircraft to a maintenance facility for maintenance based on a maintenance priority of the maintenance priorities assigned to the aircraft.