Automated Device Grading With Controlled Imaging for Screen Damage
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Solution Overview
Problem
Existing systems for grading pre-owned electronic devices rely heavily on manual labor, which is costly, slow, and inaccurate, and often fail to capture high-quality standardized images, leading to customer disputes.
Innovation Solution
A multi-stage automated assembly line system that includes stations for scanning, identifying device models, grading screens and cameras, and assessing cosmetic damage, utilizing AI programs to analyze images and determine grades, and sorting devices based on these assessments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual labor is used to inspect, sort, and grade pre-owned electronic devices, then the process can be performed with simple equipment, but it is costly, slow, and inaccurate
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated optical inspection system that uses image capture devices, lighting systems, and AI-based image analysis to detect defects, cracks, and cosmetic damage on device surfaces, thereby improving grading accuracy while eliminating manual labor
Solution Approach 2:
The system enables devices to be automatically graded without human intervention by using machine learning models that autonomously analyze captured images, identify defects, and assign grades based on pre-established criteria, making the system self-sufficient in the grading process
2Productivity
If manual inspection is used, then equipment complexity is low, but the process is slow and productivity is reduced
Solution Approach 1:
The patent replaces slow manual inspection with high-speed automated image capture and processing systems that can analyze multiple devices simultaneously, using conveyor belts to move devices through inspection stations, thereby dramatically increasing grading throughput and productivity
Solution Approach 2:
The system performs preliminary actions by pre-positioning lighting systems, image capture devices, and conveyor belt configurations before devices arrive, and by pre-training AI models with extensive defect data, enabling rapid automated inspection without manual setup for each device
3Measurement precision
If manual grading is used, then the system is simple to operate, but image capture quality is poor leading to customer disputes
Solution Approach 1:
The patent replaces manual image capture with automated optical systems that use controlled lighting environments, high-resolution cameras, and standardized positioning fixtures to capture consistent, high-quality images of devices from multiple angles, eliminating variability introduced by manual operations
Solution Approach 2:
The system employs universal image capture protocols and standardized lighting configurations that work across different device types and models, enabling the same automated system to grade various electronic devices with consistent image quality without requiring operator expertise
Data Source
AI summary
Systems and methods for automatically grading a user device are provided. Such systems and methods can include (1) a lighting element positioned at an angle relative to a platform, (2) an imaging device positioned at the angle relative to the platform such that light emitted from the lighting element and a field of view of the imaging device form a right angle where the light emitted from the lighting element and the field of view meet at a user device when the user device is positioned at a predetermined location on the platform, and (3) control circuitry that can activate the lighting element, instruct the imaging device to capture an image of a screen of the user device while the user device is at the predetermined location and is being illuminated by the first lighting element, and parse the image to determine whether the screen is damaged.