Optical Calibration Fixture for Precise Substrate Transfer Robot Alignment
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Solution Overview
Problem
Conventional robot calibration methods in substrate processing systems are prone to human error and system variations, such as vacuum deflections, making accurate placement of substrates and edge rings challenging.
Innovation Solution
A robot calibration system that includes a calibration fixture with multiple cameras mounted on a substrate processing chamber, which captures images of a test substrate and edge ring to measure distances and calculate the center, allowing for precise calibration of the robot by determining pixel width and reference markings, and updating robot coordinates to achieve accurate alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional robot calibration methods are used, then the calibration process is simple, but the calibration accuracy is low due to human error and system variations
Solution Approach 1:
The patent replaces manual mechanical calibration methods with an automated optical measurement system using cameras and image processing. The controller automatically captures images, processes them to identify substrate and edge ring positions, and calculates calibration parameters, eliminating human error and mechanical variability in the calibration process
Solution Approach 2:
The patent creates a digital copy of the physical calibration scene by capturing images with cameras. These image copies are then processed to extract precise positional information about the substrate and edge ring, allowing for accurate measurement without direct physical contact or manual intervention
2Manufacturing precision
If manual calibration methods are used, then the system is easy to operate, but the placement accuracy of substrates and edge rings is poor
Solution Approach 1:
The calibration system performs self-calibration by automatically capturing images, processing them to identify positions, and updating robot coordinates without requiring manual intervention. The system uses its own camera and controller resources to complete the calibration process autonomously, achieving high placement accuracy while simplifying operator involvement to merely initiating the process
Solution Approach 2:
The system captures images during calibration, processes them to determine actual positions of the substrate and edge ring, compares these with expected positions, and uses this feedback information to calculate and apply correction values to the robot coordinates, thereby achieving precise placement through closed-loop control
Data Source
AI summary
A robot calibration system includes a calibration fixture configured to be mounted on a substrate processing chamber. The calibration fixture includes at least one camera arranged to capture an image including an outer edge of a test substrate and an edge ring surrounding the test substrate. A controller is configured to receive the captured image, analyze the captured image to measure a distance between the outer edge of the test substrate and the edge ring, calculate a center of the test substrate based on the measured distance, and calibrate a robot configured to transfer substrate to and from the substrate processing chamber based on the calculated center of the test substrate.