AI Dimension Error Detection Using Image Copying
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Solution Overview
Problem
Current methods for detecting dimension errors in manufacturing, such as those in the ceramics industry, require expensive sensors and lighting equipment and often need user intervention, limiting their applicability and precision.
Innovation Solution
A method and apparatus using artificial intelligence that captures images with a robot arm or conveyor-mounted camera, estimates dimensional data, and determines dimension errors through learned models without the need for expensive devices or user input, utilizing image processing and depth estimation to identify errors in 2D and 3D images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If physical sensors are used for dimension error detection, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent uses image copying technology where a 2D image of the object is captured and processed to extract dimensional information. Instead of using complex physical sensors, the system creates a digital copy (image) of the object and analyzes it to obtain measurement data, thereby simplifying the device while maintaining measurement capability
Solution Approach 2:
The patent replaces mechanical/physical sensor systems with an optical-digital system. A camera captures images and AI algorithms process these images to extract dimensional data, substituting the mechanical measurement approach with an optical-digital approach that reduces device complexity
2Measurement precision
If multiple cameras and lighting equipment are used for image-based dimension measurement, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The system uses a single camera to capture a 2D image copy of the object, which is then processed through AI algorithms to extract dimensional information. This digital copying approach eliminates the need for multiple cameras and complex lighting equipment while maintaining measurement precision
Solution Approach 2:
The patent employs a simple, inexpensive camera setup rather than expensive, complex imaging systems. The approach uses readily available camera technology combined with software processing, replacing costly hardware with more affordable components
3Measurement precision
If traditional image analysis methods are used for dimension measurement, then measurement precision is improved, but ease of operation deteriorates due to user intervention requirements
Solution Approach 1:
The system performs automatic dimension measurement and error detection without requiring user intervention. The AI model automatically processes the captured image, extracts dimensional data, and identifies dimension errors, enabling the system to serve itself and eliminating the need for manual operation
Solution Approach 2:
The patent implements an automated feedback loop where the AI model continuously processes images, compares measured dimensions against standard values, and automatically identifies dimension errors. This feedback mechanism operates without user intervention, improving ease of operation while maintaining precision
4Measurement precision
If expensive sensors and lighting equipment are installed for high-precision dimensional measurement, then measurement precision is improved, but ease of manufacture deteriorates
Solution Approach 1:
The system uses digital image copying and AI processing to achieve precise dimensional measurement without requiring expensive physical sensors. By creating and analyzing digital copies of the object, the system simplifies manufacturing implementation while maintaining measurement precision
Solution Approach 2:
The patent replaces complex mechanical sensor systems with an optical-digital system using standard cameras and AI software. This substitution makes the system easier to manufacture and implement, as it avoids the need for specialized expensive hardware while achieving comparable or superior measurement precision
Data Source
AI summary
An apparatus for detecting a dimension error obtains an image of a target object, estimates dimensional data for a region of interest (ROI) for which dimensions are to be measured from the image of the target object using a learned dimensional measurement model, and determines whether there is a dimension error in the ROI from the estimated dimension data using a learned dimension error determination model.