3D Assembly Inspection Mapping for Stage-Aware Quality Control
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Solution Overview
Problem
Manual inspection of complex structures, such as aircraft assembly, is prone to human error, is time-consuming, and costly, and requires extensive disassembly to identify issues, which is inefficient and costly.
Innovation Solution
An automated supervision and inspection system using a computer system that generates a three-dimensional global map of the assembly site and processes sensor data to identify the current stage of the assembly process, context, and quality report, reducing the need for human intervention and enabling efficient identification of issues without extensive disassembly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection is used to inspect assembly quality, then human operators can identify issues, but human error increases and inspection accuracy decreases
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated optical inspection system that uses sensors, cameras, and image processing algorithms to detect assembly defects. This substitution eliminates human error and significantly improves inspection accuracy through consistent, repeatable measurements and advanced image analysis capabilities.
Solution Approach 2:
The inspection system performs self-verification by automatically capturing images, processing them through algorithms, identifying defects, and generating inspection reports without human intervention. The system serves itself by autonomously completing the entire inspection workflow from data acquisition to defect classification.
2Reliability
If manual inspection is used to identify assembly issues, then problems can be detected, but inspection time increases and productivity decreases
Solution Approach 1:
The automated inspection system operates continuously without interruption, capturing images and processing data in real-time as assemblies move through the production line. Multiple sensors and processors work simultaneously and continuously, eliminating the pauses and sequential operations inherent in manual inspection methods.
Solution Approach 2:
The system uses excessive computational resources and multiple redundant sensors to perform inspection tasks that would take a single human operator much longer. Parallel processing of multiple images and defect types occurs simultaneously, providing comprehensive inspection coverage far exceeding manual capabilities.
3Reliability
If manual inspection is used to detect assembly defects, then issues can be identified, but disassembly requirements increase and costs increase
Solution Approach 1:
The inspection system performs defect detection early in the assembly process before components are fully assembled or painted. By conducting inspection at this preliminary stage, the system identifies issues when they are most easily corrected, eliminating the need for time-consuming disassembly and repainting operations that would be required if defects were discovered later.
4Ease of operation
If manual inspection methods are used, then inspection can be performed, but labor costs increase and operational costs increase
Solution Approach 1:
The patent replaces expensive manual labor with an automated inspection system that, while requiring significant initial investment, eliminates ongoing labor costs and reduces operational expenses through consistent, high-volume inspection capabilities. The system pays for itself by eliminating the need for multiple trained inspectors and reducing rework costs.
Data Source
AI summary
A method and apparatus for performing automated supervision and inspection of an assembly process. The method is implemented using a computer system. Sensor data is generated at an assembly site using a sensor system positioned relative to the assembly site. A three-dimensional global map for the assembly site and an assembly being built at the assembly site is generated using the sensor data. A current stage of an assembly process for building an assembly at the assembly site is identified using the three-dimensional global map. A context for the current stage is identified. A quality report for the assembly is generated based on the three-dimensional global map and the context for the current stage.


