Substrate Transport Auto-Teaching via Eccentricity-Based Station Alignment
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Solution Overview
Problem
Existing substrate processing systems face challenges in automatically teaching substrate transport robots the precise location of substrate holding stations within processing equipment without disrupting the environment or requiring additional instrumentation and software changes, especially in vacuum environments.
Innovation Solution
The system employs existing substrate processing sensors and commands to automatically locate substrate holding stations using a teaching substrate with a smaller size, inducing eccentricity to determine the station location, and utilizes deterministic station features to iteratively adjust the position, ensuring precise alignment without external modifications or software changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If teaching sensors are added to the substrate processing equipment, then the substrate transport robot can be taught precise locations, but the device complexity increases and additional instrumentation is required
Solution Approach 1:
The substrate processing equipment uses its own existing sensors and processing capabilities to automatically teach the robot locations, without requiring external teaching sensors. The system serves itself by utilizing deterministic station features and existing substrate processing sensors to determine precise positions autonomously
Solution Approach 2:
The system creates a virtual model of the substrate holding station locations by processing images of deterministic features, rather than physically measuring positions with dedicated teaching sensors. This digital copying approach eliminates the need for additional physical instrumentation
2Measurement precision
If sensors are placed in vacuum environment for teaching, then positioning can be achieved, but the reliability of sensors in vacuum conditions deteriorates
Solution Approach 1:
The system introduces deterministic station features (such as fiducial markers or geometric features on the substrate holder) as intermediaries between the robot and the vacuum environment. These features can be detected from outside the vacuum or through vacuum-compatible optical means, eliminating the need for electronic sensors inside the vacuum chamber
Solution Approach 2:
The patent replaces electronic sensor-based teaching systems with optical/image-based detection methods. By using cameras or optical sensors to capture images of deterministic features and processing these images to determine positions, the system avoids placing electronic sensors in the vacuum environment where they would be unreliable
3Measurement precision
If teaching is performed manually with sensors and fixtures, then location accuracy is achieved, but the loss of time for teaching and machine downtime increases
Solution Approach 1:
The system performs automatic teaching by having the robot autonomously navigate to substrate holding stations and capture images of deterministic features. This preliminary automatic teaching action eliminates the need for subsequent manual teaching adjustments, reducing overall teaching time and machine downtime
Solution Approach 2:
The system implements an automatic feedback loop where the robot captures images of deterministic features, the image processing system determines position deviations, and the robot automatically adjusts its positions based on this feedback. This closed-loop automatic teaching process eliminates time-consuming manual intervention while maintaining high positioning precision
4Extent of automation
If additional instrumentation is added to the substrate processing equipment, then teaching capability is improved, but the ease of manufacture deteriorates due to modifications required
Solution Approach 1:
The system uses existing substrate processing sensors and imaging capabilities for dual purposes: both for normal substrate processing and for automatic teaching of robot positions. This multi-functionality eliminates the need for separate dedicated teaching instrumentation, maintaining ease of manufacture while achieving full automatic teaching capability
Data Source
AI summary
A substrate transport apparatus auto-teach system for auto-teaching a substrate station location, the system including a frame, a substrate transport connected to the frame, the substrate transport having an end effector configured to support a substrate, and a controller configured to move the substrate transport so that the substrate transport biases the substrate supported on the end effector against a substrate station feature causing a change in eccentricity between the substrate and the end effector, determine the change in eccentricity, and determine the substrate station location based on at least the change in eccentricity between the substrate and the end effector.