Transfer Robot Vision Teaching for Precise Chamber Alignment
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Solution Overview
Problem
Manual teaching methods for transfer devices in semiconductor manufacturing are prone to safety accidents and require extensive time due to visual observation and manual alignment, leading to inefficiencies.
Innovation Solution
Implement a teaching method using vision image processing with an ADAS technique to derive precise position coordinates for transfer robots, incorporating a vision camera and image analysis unit to automate the teaching process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual teaching method with visual observation is used, then the operator can perform teaching operation, but safety accident may occur and teaching time increases
Solution Approach 1:
The patent replaces the manual mechanical teaching operation with an automated vision-based system. The vision camera captures images of the chamber, and image processing algorithms automatically identify target positions and generate teaching data, eliminating the need for operators to manually enter the chamber and observe visual alignment.
Solution Approach 2:
The patent introduces a vision camera and image processing system as an intermediary between the operator and the teaching target. This intermediary captures visual information and processes it to determine precise positions, allowing the operator to perform teaching operations from outside the chamber while maintaining accuracy.
2Ease of operation
If manual teaching operation inside chamber is performed, then teaching can be completed, but it takes long time to finish task
Solution Approach 1:
The patent replaces manual visual alignment operations with automated image processing. The system captures images using a vision camera and uses algorithms to automatically identify target positions, significantly reducing the time required for teaching operations while maintaining ease of use.
Solution Approach 2:
The patent enables the system to perform teaching operations autonomously. The vision camera and image processing unit automatically capture images, identify positions, and generate teaching data without requiring continuous manual intervention, thereby improving productivity while keeping the operation simple.
3Measurement precision
If vision image processing with ADAS technique is used, then positioning precision improves, but device complexity increases
Solution Approach 1:
The patent introduces a vision camera and image processing unit as intermediaries to achieve high positioning precision. These components capture images and process them to extract precise position coordinates, providing accurate measurement without requiring complex mechanical positioning systems.
Solution Approach 2:
The patent replaces complex mechanical positioning and measurement systems with a vision-based system. The ADAS image processing techniques enable precise position detection through software algorithms, reducing the need for complex mechanical structures and sensors.
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 high-precision positioning and reduces the risk of safety accidents while significantly minimizing teaching work time.
Implementation Method 1
acquiring a first image through a vision camera installed in the transfer robot
Implementation Method 2
reading the acquired image data, specifying the transfer target object preset to a teaching target, and deriving a first position coordinate for the transfer target object
Data Source
AI summary
The present invention provides a teaching method of transfer equipment. The teaching method of transfer equipment comprises: a) installing a transfer robot in a groove position of a transfer chamber in which transfer target objects with a transferred object transferred are arranged; b) acquiring a first image through a vision camera installed in the transfer robot in a home position, reading the acquired image data, specifying the transfer target object preset to a teaching target, and deriving a first position coordinate for the transfer target object; c) moving the transfer robot to a position corresponding to the first position coordinate; and d) acquiring a second image for the transfer target object through the vision camera from the first position coordinate, and deriving a second position coordinate by reading the acquired image data.


