Aircraft Component Record Processing via NLP Structuring
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Solution Overview
Problem
The scattered and unstructured nature of aircraft component maintenance records complicates efforts to holistically understand the maintenance conditions of aircraft components and predict maintenance needs, leading to potential disruptions in aircraft operations and increased passenger exposure to damaged components.
Innovation Solution
A method involving the loading of unstructured aircraft component records into computer memory, processing them with a natural language processing (NLP) model to generate structured Component, Condition, and Location (CCL) records, and then aggregating and analyzing these records to determine time-dependent failure distributions for specific component types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If unstructured maintenance records are collected from multiple sources, then the quantity of maintenance information is improved, but the complexity of data processing and analysis worsens
Solution Approach 1:
The patent introduces an NLP model as an intermediary between unstructured maintenance records and structured analysis. The model converts free-text maintenance records into standardized CCL records with predefined fields (component, condition, location), acting as a mediator that transforms heterogeneous data into a uniform format suitable for aggregation and analysis.
Solution Approach 2:
The patent transforms maintenance records by changing their parameter structure from unstructured free text to structured fields with specific parameters (component ID, condition type, location coordinates). This parameter transformation enables systematic aggregation and comparison across different data sources while maintaining the original information content.
2Reliability
If maintenance records are aggregated and analyzed in real-time, then the reliability of maintenance status information is improved, but the processing time and computational resources worsen
Solution Approach 1:
The patent performs preliminary structuring of maintenance records using NLP models before aggregation is needed. By pre-converting unstructured records into standardized CCL format as they are collected, the system prepares data for rapid aggregation and analysis when maintenance decisions are required, reducing real-time processing demands.
Data Source
AI summary
A method for aircraft maintenance comprises loading, into computer memory, a plurality of unstructured aircraft component records originating from one or more different component status monitors, the plurality of unstructured aircraft component records describing observed maintenance conditions of a plurality of different aircraft components. The plurality of unstructured aircraft component records are provided from computer memory to a natural language processing (NLP) model configured to output a corresponding plurality of digital component, condition, and location (CCL) records for the plurality of different aircraft components. CCL records for a plurality of different CCL types are independently computer aggregated. The CCL records for a selected CCL type are computer aggregated to determine a time-dependent failure distribution for the selected CCL type.