Optical Inspection Measurement Mapping Across Multiple Assembly Units
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Solution Overview
Problem
Current optical inspection systems lack the ability to automatically generate a common measurement across multiple assembly units and efficiently configure optical inspection stations along an assembly line, leading to inefficiencies in defect detection and quality control.
Innovation Solution
The system retrieves images from optical inspection stations, identifies serial numbers and positions of assembly units, and generates a virtual representation of the assembly line, enabling real-time configuration and defect detection by using machine vision techniques to analyze images and metadata, and applying homography transforms to correct for optical distortions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual configuration and measurement methods are used for optical inspection stations, then flexibility and adaptability are maintained, but productivity and efficiency are reduced due to time-consuming manual processes
Solution Approach 1:
The system automatically configures optical inspection stations by detecting assembly units and generating measurement specifications without manual intervention. The computer system retrieves images, identifies features, and configures measurement parameters autonomously, allowing the system to serve itself rather than requiring operator configuration for each inspection station.
Solution Approach 2:
The system performs preliminary configuration actions by pre-configuring measurement specifications and inspection parameters before actual inspection begins. By automatically generating measurement specifications from detected assembly unit features, the system prepares inspection settings in advance, eliminating the need for manual configuration during production.
2Adaptability or versatility
If multiple separate measurement systems are used for different assembly units, then measurement coverage is comprehensive, but device complexity and coordination requirements increase
Solution Approach 1:
A single optical inspection station is configured to inspect multiple different assembly units by automatically adapting measurement specifications. The computer system retrieves images of different assembly units, identifies their specific features, and generates appropriate measurement specifications for each, allowing one inspection station to perform multiple inspection functions rather than requiring separate dedicated systems for each assembly unit type.
Solution Approach 2:
The measurement configuration is made dynamic and adaptable rather than static and fixed. The system automatically adjusts measurement specifications based on the detected assembly unit type and features, allowing the inspection parameters to change dynamically with each assembly unit inspected. This eliminates the need for manual reconfiguration and complex coordination between multiple fixed measurement systems.
3Measurement precision
If manual measurement specification generation is used, then measurement accuracy can be controlled by experts, but loss of time and productivity are significant
Solution Approach 1:
The manual mechanical process of expert measurement specification creation is replaced with an automated computer-based system. The computer system uses image processing and feature detection algorithms to automatically generate measurement specifications, substituting automated computational processes for manual expert analysis. This maintains measurement accuracy through algorithmic precision while eliminating the time loss associated with manual configuration.
Solution Approach 2:
The system introduces an intermediary computer-based image analysis process between the assembly unit and the measurement specification. Instead of direct manual measurement, the computer system retrieves images, detects features, and generates measurement specifications as an automated intermediary step. This intermediary process maintains measurement accuracy through systematic analysis while dramatically reducing the time required compared to direct manual measurement.
4Manufacturing precision
If optical inspection stations are configured without automatic assembly unit detection, then setup flexibility is maintained, but measurement precision and positioning accuracy deteriorate
Solution Approach 1:
The optical inspection station automatically detects assembly units and configures itself without manual positioning or setup. The computer system retrieves images, identifies assembly unit features, and automatically configures measurement parameters and positioning, allowing the system to self-configure rather than requiring manual setup. This maintains positioning accuracy through automated detection while simplifying operation by eliminating manual configuration steps.
Solution Approach 2:
The system performs preliminary detection and configuration actions before measurement begins. By automatically detecting assembly units and generating measurement specifications in advance, the system prepares accurate positioning and measurement parameters beforehand. This preliminary automated detection ensures positioning accuracy is achieved without requiring manual setup or complex configuration procedures during operation.
Data Source
AI summary
One variation of a method for automatically generating a common measurement across multiple assembly units includes: displaying a first image—recorded at an optical inspection station—within a user interface; receiving manual selection of a particular feature in a first assembly unit represented in the first image; receiving selection of a measurement type for the particular feature; extracting a first real dimension of the particular feature in the first assembly unit from the first image according to the measurement type; for each image in a set of images, identifying a feature—analogous to the particular feature—in an assembly unit represented in the image and extracting a real dimension of the feature in the assembly unit from the image according to the measurement type; and aggregating the first real dimension and a set of real dimensions extracted from the set of images into a digital container.