Conveyor Imaging for Automated Mobile Device Defect Grading
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Solution Overview
Problem
Mass production of user devices often results in defects and damages that go undetected due to inefficient and error-prone manual inspection methods.
Innovation Solution
A modular system with imaging devices positioned around conveyors captures image data to determine device type and defects, using machine learning to predict functional defects based on aesthetic ones, and assigns grades or scores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection methods are used to detect defects, then operational simplicity is maintained, but measurement precision and reliability of defect detection deteriorate
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated imaging system that captures images of user devices and uses image processing algorithms to detect defects. The system substitutes human visual inspection with computational analysis, significantly improving measurement precision while maintaining manageable system complexity through software-based solutions.
Solution Approach 2:
The patent creates digital copies (images) of the physical user devices for inspection purposes. By capturing images and analyzing them computationally, the system enables precise defect detection without requiring direct physical handling, thereby improving accuracy while keeping the inspection process efficient and scalable.
2Productivity
If manual inspection is used, then device complexity remains low, but productivity and inspection speed deteriorate
Solution Approach 1:
The patent replaces slow manual inspection processes with automated imaging and image processing systems that can analyze multiple devices rapidly. This substitution enables high-throughput inspection while managing complexity through standardized software pipelines and automated workflows.
Solution Approach 2:
The patent implements continuous inspection capabilities where devices are systematically imaged and analyzed in sequence without interruption. The automated system maintains continuous operation, processing devices as they move through the inspection area, thereby maximizing productivity while keeping the system architecture manageable through streamlined processes.
3Measurement precision
If comprehensive defect detection is implemented, then measurement precision improves, but loss of time in processing increases
Solution Approach 1:
The patent implements a multi-level inspection approach where the system first performs rapid initial screening to identify obvious defects, then applies more comprehensive analysis only to devices that require detailed examination. This partial application of thorough inspection methods maintains high accuracy for critical cases while reducing overall processing time for the entire batch.
Solution Approach 2:
The patent divides the inspection process into multiple stages: initial image capture, preliminary defect screening, and detailed analysis of suspicious areas. By segmenting the inspection workflow, the system achieves comprehensive defect detection accuracy while minimizing total processing time through efficient allocation of computational resources to different inspection stages.
Data Source
AI summary
Methods and systems are disclosed for grading user devices (e.g., mobile devices, smartphones, IoT devices, electronic devices, etc.). Image data associated with one or more portions of a user device may be determined as the user device traverses a conveyor system. The image data may be analyzed and a graphical depiction of regions of the user device where defects are present may be generated to rank, score, and/or grade the user device and/or portions of the user device.