A leading component recycling firm sought to streamline and automate the identification and valuation of components using computer vision (CV) technology. The project aimed to increase efficiency, accuracy, and reduce operational costs by accurately estimating the recoverable precious metals within each component.
Objectives
Automated Identification: CV system accurately identifies catalytic converter components.
Precise Valuation: Reliable estimation of preciousmetal content for accurate pricing.
Seamless Integration: Fully integrates with existinginfrastructure, improving efficiency.
Challenges
Component Recognition: Accurate identification of various component types.
Metal Estimation: Precise calculation of precious metal content.
System Integration: Seamless integration with existing company systems.
Solutions
Computer Vision Implementation
A CV system was developed to analyze 3D images, classify components by type, and assess precious metal content with high accuracy.
Mobile Application Integration
The system was integrated with a mobile app, enabling users to scan components quickly using smartphones.
High-Speed Processing
The system identifies 500 common components with 90%+ accuracy in under 3 seconds and can handle up to 10,000 less common types with adequate training, boosting efficiency and reducing manual effort.
Benefits
Increased Accuracy: Enhanced pricing and metal estimation accuracy.
Faster Processing: Quicker valuation times.
Cost Reduction: Lower operational costs and reduced need for manual labor.
Key results
98% Accuracy
Achieved over 98% accuracy in recognizing 500 common component types within 3 seconds.
30% Faster Processing
Significantly reduced valuation time through high-speed processing, improving overall efficiency.
20% Cost Reduction
Lowered operational costs by reducing the need for manual labor and minimizing errors.
Enhanced System Integration
CV system seamlesslyintegrated with existing infrastructure, improvedworkflow.
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