Aircraft Coordinate Database for Robotic Fastener Tracking
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Solution Overview
Problem
The transition from manual to automated fastener installation, removal, and replacement in aircraft maintenance poses challenges in recording and storing precise data, especially when transitioning between different fastener types and drilling tools, which affects the structural integrity and efficiency of aircraft maintenance.
Innovation Solution
A system that generates and stores fastener characteristics in a digital thread, using a data structure that connects elements like fastener characteristics, allowing robots to collect and analyze digital information during tasks, and use it for future jobs, optimizing robotic maintenance and performance through a hierarchical data structure that includes virtual representation, machine learning, and robot job-based sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual fastener installation and removal processes are transitioned to automated robotic processes, then productivity and consistency are improved, but the complexity of data recording and coordination between different robots increases
Solution Approach 1:
The patent creates a universal database system that serves multiple functions: storing fastener characteristics, tracking aircraft lifecycle data, coordinating between different robots, and providing predictive analytics. This single multi-functional database structure replaces multiple separate data recording systems, managing complexity while enabling automated maintenance across different aircraft components and robot types.
Solution Approach 2:
The patent implements a hierarchical nested data structure where fastener-level data is nested within aircraft-component-level data, which is nested within aircraft-level data. This nested organization allows robots to access appropriate data granularity for their specific tasks while maintaining a unified coordinate system, managing complexity through structured nesting rather than flat monolithic data storage.
2Adaptability or versatility
If different types of fasteners and drilling tools are used throughout the aircraft lifecycle, then adaptability is improved, but measurement precision and data consistency deteriorate
Solution Approach 1:
The patent transforms physical fastener characteristics (position, orientation, dimensions) into standardized digital parameters stored in a unified coordinate system. By converting diverse physical fastener types into consistent digital representations with standardized parameters, the system maintains measurement precision across different fastener and tool types while preserving adaptability to handle various aircraft maintenance scenarios.
Solution Approach 2:
The patent creates digital copies (digital twins) of physical fasteners and their characteristics in a virtual database. These digital copies preserve precise positional and dimensional information regardless of the physical fastener type or tool used, enabling consistent measurement and tracking across different aircraft components and maintenance operations without being constrained by physical variations.
3Reliability
If fastener data is tracked throughout the entire aircraft lifecycle, then reliability is improved, but loss of time for data collection and processing increases
Solution Approach 1:
The patent performs preliminary data collection and processing by maintaining continuous tracking of fastener characteristics and aircraft maintenance history in the database before actual maintenance operations. This preliminary preparation of data allows robots to quickly retrieve and utilize pre-processed information during maintenance tasks, reducing real-time data processing time while maintaining comprehensive lifecycle tracking for reliability assessment.
Solution Approach 2:
The patent implements feedback mechanisms where the database continuously receives updated fastener and aircraft data, processes it, and provides refined information back to maintenance operations. This ongoing feedback loop enables the system to learn from accumulated data, improve predictive analytics over time, and provide increasingly accurate recommendations without requiring proportional increases in data processing time for each operation.
Data Source
AI summary
Techniques are described herein for generating a database. A method can include receiving a first value associated with a physical element of a target object and obtained during a performance of a first stage of a robot task, and a second value associated with the physical element and obtained during a second stage, wherein the first and second value describe a same characteristic of the physical element and are represented in a target object coordinate system. A third value associated with a tool of a robot and obtained during a third stage can be received, wherein the third value is represented in the robot coordinate system. A first data structure can be generated, wherein the first data structure comprises the first, second, and third value. The first data structure can be associated with a second data structure, wherein the second data structure comprises a fourth value identifying the target object.