Aircraft Engine Compliance Assessment via Digital Thread
Solution Overview
Problem
Existing tools for validating compliance of aircraft engine field data with design assumptions are inefficient and time-consuming, particularly due to the complexity of temporal data representing operational parameters that change during flight missions.
Innovation Solution
A method and system for assessing compliance using a digital thread platform that compares field time-series profiles with design time-series profiles through a similarity metric, generating a compliance assessment based on the difference between actual and expected statistics, accounting for sequence, duration, and amplitude of operational parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing tools are used to validate compliance of field data with design assumptions, then compliance validation can be performed, but the process is inefficient and time-consuming
Solution Approach 1:
The patent replaces manual compliance validation processes with an automated computational system that uses machine learning models and digital thread technology. The system automatically ingests field data, compares it against design assumptions, and generates compliance assessments without manual intervention, thereby maintaining validation accuracy while dramatically reducing time consumption.
Solution Approach 2:
The patent creates a digital replica (digital thread) of the aircraft engine's entire lifecycle data, including design assumptions, test data, and field data. This digital copy enables automated comparison and compliance validation without requiring physical inspection or manual analysis of actual engine data, thus speeding up the validation process while maintaining precision.
2Measurement precision
If manual compliance assessment is performed, then detailed analysis can be conducted, but the process requires significant manual effort
Solution Approach 1:
The patent implements a self-service compliance assessment system where the digital thread platform automatically performs data ingestion, processing, comparison, and compliance determination. The system uses pre-configured design assumptions and automated algorithms to assess compliance without requiring manual analysis, thereby eliminating manual effort while maintaining assessment accuracy through systematic computational methods.
Solution Approach 2:
The patent incorporates feedback mechanisms where the system continuously compares field data against design assumptions and provides automated compliance feedback. This feedback loop enables the system to self-correct and refine compliance assessments automatically, reducing the need for manual intervention while maintaining high accuracy through iterative computational validation.
3Measurement precision
If comprehensive field data analysis is performed to distinguish compliant and non-compliant utilization, then accurate compliance determination is achieved, but the complexity of temporal data increases processing difficulty
Solution Approach 1:
The patent introduces a digital thread as an intermediary layer between raw field data and compliance determination. This digital thread structures and organizes temporal data from multiple sources (design assumptions, test data, field data) into a standardized format, making the data more manageable and easier to process while maintaining the comprehensive information needed for accurate compliance determination.
Solution Approach 2:
The patent segments the complex compliance assessment process into distinct modular components: data ingestion, data processing, comparison against design assumptions, and compliance determination. Each module handles specific aspects of the analysis independently, reducing overall processing complexity while maintaining comprehensive analysis capability through systematic breakdown of the assessment workflow.
Data Source
AI summary
Methods and systems for assessing compliance of aircraft engines are described. The method comprises selecting a test population from a set of deployed aircraft engines based on one or more selection criteria, each of the deployed aircraft engines having associated thereto design requirements and field data; selecting at least one parameter that is present in both the design requirements and the field data of the test population, the design requirements comprising design time-series profiles, the field data comprising field time-series profiles; comparing the field time-series profiles to the design time-series profiles for the at least one parameter using a similarity metric to obtain field statistics; comparing the field statistics to expected statistics from the design requirements; and generating a compliance assessment output of the test population based on a difference between the field statistics and the expected statistics.