Automated Secondhand Textile Inspection for Resale Sorting
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Solution Overview
Problem
Current methods for processing secondhand textiles are labor-intensive, time-consuming, and prone to errors due to manual handling and visual inspection, which affects the accuracy of determining attributes and quality, limiting the efficient utilization of secondhand textiles.
Innovation Solution
An automated method using inspection and screening hardware, such as laser sensors, infrared cameras, and AI processors, to determine attribute data and quality of secondhand textiles, enabling automated sorting and tagging for resale or recycling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual handling and visual inspection is used to process secondhand textiles, then employees can determine attributes and quality of each item, but the process becomes labor-intensive and time-consuming
Solution Approach 1:
The patent replaces manual mechanical inspection with automated optical and sensing systems. Image capture devices, laser sensors, and infrared cameras automatically detect textile attributes such as material composition, color, size, and defects, eliminating the need for manual handling while maintaining or improving measurement accuracy.
Solution Approach 2:
The patent introduces an intermediary automated inspection system that acts as a mediator between the textiles and the decision-making process. This system includes image processing algorithms and data analysis components that interpret sensor data to determine textile attributes and quality, bridging the gap between raw sensory data and actionable classification decisions.
2Reliability
If manual visual inspection is used to determine textile quality, then employees can assess salability based on wear and damage, but errors and oversights occur due to human fatigue and subjectivity
Solution Approach 1:
The patent replaces subjective human visual assessment with objective automated sensing systems. Multiple sensors including image capture devices, laser sensors for material identification, and infrared cameras for detecting stains and defects provide consistent, repeatable measurements that eliminate human fatigue and subjectivity while improving defect detection accuracy.
Solution Approach 2:
The patent implements feedback mechanisms where the automated inspection system continuously analyzes textile attributes and provides real-time classification decisions. The system uses image processing algorithms that compare detected features against predefined quality criteria, providing consistent feedback on salability determinations that can be validated and adjusted based on accumulated data.
3Productivity
If automated inspection hardware is used to process secondhand textiles, then processing efficiency and accuracy improve, but device complexity increases
Solution Approach 1:
The patent employs multi-functional inspection hardware that can perform multiple detection tasks simultaneously. For example, image capture devices serve both for visual inspection and material identification, while laser sensors provide both material composition analysis and defect detection. This reduces the number of separate devices needed and simplifies the overall system architecture.
Solution Approach 2:
The patent combines multiple sensing functions into integrated inspection stations. Image capture devices, laser sensors, and infrared cameras are merged into a coordinated system that processes textiles through a single pass, eliminating the need for multiple separate inspection stages and reducing operational complexity.
4Loss of information
If comprehensive attribute data is collected from each secondhand textile, then resale value determination improves, but processing time increases due to detailed inspection requirements
Solution Approach 1:
The patent implements continuous automated inspection where textiles move through the system on conveyors while being scanned by multiple sensors simultaneously. The inspection process occurs continuously without interruption, capturing all necessary attribute data in a single pass rather than through multiple sequential manual examination steps.
Solution Approach 2:
The patent performs preliminary automated data collection using non-contact sensors before any physical handling or detailed examination. Image capture devices and laser sensors gather comprehensive attribute information including material composition, color, size, and visible defects in advance, allowing for rapid initial classification and reducing the need for time-consuming manual verification.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Facilitates efficient, accurate, and scalable processing of secondhand textiles with minimal human interaction, enhancing their utilization and reducing textile waste by automating the determination of attributes and quality.
Implementation Method 1
inspection and screening hardware, such as laser sensors
Implementation Method 2
infrared cameras
Data Source
AI summary
A method of processing secondhand textiles for further utilization includes providing a secondhand textile, inspecting and screening the secondhand textile, with at least inspection and screening hardware, to determine attribute data of the secondhand textile, analyzing the determined attribute data of the secondhand textile, and determining if the secondhand textile is salable or non-salable based on at least the analyzing of the determined attribute data of the secondhand textile.