Training Program Generation Using Operational Data Analysis

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Solution Overview

Problem

Existing training programs for systems, such as aircraft, often become outdated due to progressive changes in design, automation, and reliability, failing to incorporate up-to-date training and operational data.

Innovation Solution

A method and system that utilize computing systems to determine training programs for individuals based on their training history, operation history, and current equipment, by calculating training skill scores and operation skill scores, and generating anomalous state probability profiles to specify required training courses.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If training programs are developed for new equipment and system improvements, then training relevance and safety are improved, but training program updates become more complex and time-consuming

Engineering Contradiction:

Improvetraining safetyVSAvoidtraining program update complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system continuously monitors operational data from equipment and compares it against training program content to identify discrepancies. This feedback loop automatically triggers updates to training programs when operational changes are detected, ensuring training remains relevant without manual intervention.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The training development system automatically analyzes operational data, identifies training gaps, and generates updated training content without requiring manual analysis. The system serves itself by using operational data to drive training program updates, reducing the burden on human developers.

Inventive Principle:

Principle #25Self-service

2Productivity

If training programs remain unchanged to maintain simplicity, then development time is reduced, but training content becomes outdated and less effective

Engineering Contradiction:

Improvetraining development efficiencyVSAvoidtraining content currency

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The system continuously monitors operational data from equipment and automatically updates training programs as changes occur. This continuous action ensures training content remains current without requiring periodic manual reviews, maintaining both efficiency and adaptability.

Inventive Principle:

Principle #20Continuity of useful action

Solution Approach 2:

The system proactively analyzes operational data to identify potential training gaps before they become problems. By performing preliminary analysis of operational changes, the system prepares updated training content in advance, ensuring training programs are always current when needed.

Inventive Principle:

Principle #10Preliminary action

3Measurement precision

If manual analysis of training and operational data is performed, then training program accuracy is improved, but time consumption and resource requirements increase

Engineering Contradiction:

Improvetraining program accuracyVSAvoiddata analysis time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The system replaces manual data analysis with automated computational algorithms that process operational data to identify training gaps. This substitution of mechanical manual analysis with automated digital processing maintains high accuracy while dramatically reducing time consumption and resource requirements.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20250174145A1Systems and methods for development of training programs for people based on training data and operation data

Publication Date: 2025.05.29 THE BOEING CO

AI summary

A system includes a data lake including data associated with training and operation of particular equipment. The system also includes one or more processors configured to execute instructions to use a training skill model to determine training skill scores for a member of an entity associated with use of the particular equipment, to use an operation skill model to determine operation skill scores for use of the particular equipment by the member, to use an anomalous state probability model to determine anomalous state profiles associated with the particular equipment for the member, and to use a decision engine to determine a training program for the member based on the anomalous state profiles.