Aircraft Fleet Reliability Modeling via Usage-Based Sub-Fleet Segmentation
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Solution Overview
Problem
Current methods for determining aircraft maintenance intervals rely on conservative assumptions, making it difficult to validate the reliability of aircraft fleets and extend scheduled maintenance intervals effectively, as they struggle with quantifying variability in loads and usage factors.
Innovation Solution
A statistically equivalent level of safety modeling method that identifies aircraft sub-fleets based on usage profiles, determines reliability values, applies credits to sub-fleets, and calculates baseline and post-credit fleet reliability to validate the impact on overall fleet safety, using time-dependent probability distribution functions and structural component analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conservative usage assumptions are used to determine life limits, then fleet reliability is maintained, but maintenance intervals cannot be extended effectively
Solution Approach 1:
The aircraft fleet is segmented into sub-fleets based on usage profiles, allowing differentiated maintenance strategies. Each sub-fleet is analyzed separately with its own reliability characteristics, enabling extended maintenance intervals for sub-fleets with lower actual usage compared to conservative assumptions, while maintaining overall fleet reliability through the aggregated reliability model.
2Reliability
If usage credit is determined through individual aircraft evaluation, then maintenance cost is reduced, but it is difficult to validate the reliability impact on overall fleet safety
Solution Approach 1:
The methodology implements feedback by calculating overall fleet reliability based on sub-fleet reliability values and comparing it against a threshold. This feedback mechanism validates whether usage credits applied to individual sub-fleets maintain acceptable fleet-wide safety levels, providing quantitative validation without requiring complex individual aircraft assessments for each validation case.
3Reliability
If absolute reliability assessment models are used, then component reliability is quantified, but the models are difficult to validate due to difficulty in quantifying variability in loads and usage
Solution Approach 1:
The invention changes the parameter of reliability assessment from absolute individual aircraft reliability to relative sub-fleet reliability grouping. By aggregating aircraft into sub-fleets with similar usage characteristics and assessing reliability at the sub-fleet level, the method reduces the impact of quantifying individual variability in loads and usage, while still providing meaningful reliability quantification for maintenance decision-making.
Data Source
AI summary
Systems and methods are provided for statistically equivalent level of safety modeling. One method includes identifying sub-fleets within a fleet based upon usage profiles, determining a sub-fleet reliability value for each sub-fleet, determining a baseline fleet reliability for the fleet by combining the sub-fleet reliability values on a weighted basis, applying at least one credit to at least one sub-fleet, determining a post-credit sub-fleet reliability value for each sub-fleet based upon the at least one credit, determining a post-credit fleet reliability for the fleet by combining the post-credit sub-fleet reliability values on a weighted basis, comparing the baseline fleet reliability with the post-credit fleet reliability to identify a change in fleet reliability and determining whether the change in fleet reliability is within a predetermined threshold to validate the at least one credit.