PCB Sorting by Vision-Guided Reorientation for Recycling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for selecting electronic boards for recycling are laborious, require specialized personnel, pose health and safety risks, and are inefficient due to the variable geometry and difficulty in gripping boards with vacuum heads, especially when components are facing the conveyor belt.
Innovation Solution
A plant equipped with a first artificial vision module to identify boards with components facing the conveyor belt, a gripping and movement device to orient boards for a second vision module analysis, and a control unit to sort based on component recognition, using a vacuum gripping head and manipulator robots like delta robots for secure handling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual selection of electronic boards is used, then specialized personnel can visually inspect and classify boards, but the process is laborious, time-consuming, and exposes workers to health and safety risks
Solution Approach 1:
The patent replaces the manual mechanical inspection system with an automated optical vision system. Cameras capture images of electronic boards on the conveyor belt, and image processing algorithms automatically identify components and classify boards, eliminating the need for manual visual inspection while maintaining or improving classification accuracy.
Solution Approach 2:
The system enables self-service classification where the electronic boards are automatically identified and sorted without human intervention. The vision system and control unit work together to autonomously classify boards based on component detection, freeing workers from direct involvement in the sorting process.
2Extent of automation
If vacuum gripping heads are used to handle electronic boards, then automated handling is achieved, but gripping becomes difficult when components are facing the conveyor belt due to variable geometry
Solution Approach 1:
The system performs preliminary action by detecting the orientation of electronic boards using the vision system before the gripping operation. When a board is detected with components facing the conveyor belt, the system预先 plans to rotate the board using the manipulator robot, ensuring the vacuum gripping head can effectively grasp the board from the appropriate side.
Solution Approach 2:
The patent introduces dynamic adaptability by using a manipulator robot that can rotate electronic boards to different orientations. This dynamic adjustment allows the vacuum gripping head to always approach the board from the optimal side (the side without components facing the conveyor), making the gripping operation effective regardless of the board's initial orientation.
3Object-affected harmful factors
If specialized personnel manually inspect electronic boards, then health and safety risks are present for workers, but automated systems require complex vision modules and control units
Solution Approach 1:
The patent replaces the human operator system with an automated vision and control system. Cameras, image processing units, and control algorithms work together to perform board classification, completely eliminating worker exposure to health and safety risks while managing system complexity through integrated automation.
Solution Approach 2:
The vision system and control unit act as intermediaries between the electronic boards and the sorting mechanism. Instead of direct human interaction with potentially hazardous materials, the automated system mediates the classification and sorting process, protecting workers from harmful factors while achieving the sorting objective.
4Productivity
If electronic boards are sorted based on component identification, then recycling efficiency is improved, but the process requires accurate detection of components which is challenging due to board variability
Solution Approach 1:
The patent uses an optical vision system with image processing algorithms to detect and identify components on electronic boards. This automated detection method can analyze board images to recognize component patterns, types, and arrangements, achieving accurate classification despite variations in board designs, component layouts, and manufacturing differences.
Solution Approach 2:
The system handles board variability by adjusting detection parameters and using pattern recognition algorithms that can adapt to different board types, component configurations, and imaging conditions. The vision system processes images with varying parameters to maintain consistent detection accuracy across diverse electronic board samples.
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
Enables efficient and safe automated sorting of electronic boards, reducing manual labor and health risks, improving recycling efficiency by accurately classifying and recovering valuable materials.
Implementation Method 1
said gripping head is a vacuum gripping head
Data Source
Figure 1
Figure 2~3
Figure 4~5
AI summary
Plant for classifying and sorting electronic boards (1) intended for recycling comprising a conveyor belt (3), a control unit comprising a first artificial vision module provided with at least one first camera (4), which first camera (4) is oriented towards the conveyor belt (3), a gripping and movement device (5) located downstream of the first camera (4), which gripping and movement device (5) is provided with at least one gripping head (50) and is controlled by said control unit. Said control unit comprises a second artificial vision module provided with at least one second camera (6) and configured to identify at least part of the components present on an electronic board (1) or other features of the electronic board (1), the first artificial vision module being configured to recognize the electronic boards (1) arranged with said components facing the conveyor belt and the control unit being configured to control the gripping device (5) to sequentially pick up the electronic boards (1) arranged with said components facing the conveyor belt (3) from the conveyor belt (3), to place each electronic board (1) with said components in the field of view of the second camera (6), and to sort said electronic board (1) on the basis of said components or said characteristics identified by the second artificial vision module.