Substrate-Handling Robot Self-Teaching With Sensor Wafer Feedback
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Solution Overview
Problem
Current substrate-handling robot teaching processes are time-consuming and require significant tool downtime, often involving manual intervention, which reduces throughput and accuracy.
Innovation Solution
An automated teaching method using a teaching substrate equipped with cameras, distance-measuring sensors, and wireless transceivers that wirelessly transmit sensor data to determine modified routes and station positions, allowing the substrate-handling robot to learn and adapt without human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual teaching process is used for substrate-handling robot, then teaching accuracy can be achieved through human expertise, but system downtime increases significantly and throughput decreases
Solution Approach 1:
The patent replaces manual teaching operations with an automated optical measurement system. Cameras capture images of the substrate and station markers, and computer vision algorithms automatically determine positions and routes, eliminating the need for manual intervention while maintaining high precision through digital image processing
Solution Approach 2:
The teaching system performs self-calibration and self-teaching by automatically capturing images, processing data, and determining routes without external human assistance. The robot system teaches itself by processing visual data from cameras to establish precise positions and movement paths
2Productivity
If automated teaching method is implemented, then throughput increases and system downtime decreases, but device complexity increases due to additional sensors and cameras
Solution Approach 1:
The teaching substrate serves multiple functions: it acts as a carrier for the substrate, provides reference markers for position detection, and supports camera mounting for image capture. This multi-functionality reduces the need for separate dedicated components, thereby managing device complexity while enabling automated teaching
Solution Approach 2:
The patent introduces a teaching substrate as an intermediary carrier that simplifies the automated teaching process. This substrate includes integrated markers and camera mounting structures, serving as a mediator between the robot system and the measurement process, thereby reducing overall system complexity
3Measurement precision
If automated teaching with sensor data is used, then teaching speed increases and accuracy improves, but loss of time for data processing may occur
Solution Approach 1:
The system performs preliminary actions by pre-positioning markers on the teaching substrate and pre-configuring camera angles before the actual teaching process. This preparation enables faster real-time data processing during execution, as the image processing algorithms already have optimized reference points to work with
Data Source
AI summary
A teaching substrate is loaded into a load port of an equipment front-end module (EFEM) of a fabrication or inspection tool. The EFEM includes a substrate-handling robot. The teaching substrate includes a plurality of sensors and one or more wireless transceivers. The tool includes a plurality of stations. With the teaching substrate in the EFEM, the substrate-handling robot moves along an initial route and sensor data are wirelessly received from the teaching substrate. Based at least in part on the sensor data, a modified route distinct from the initial route is determined. The substrate-handling robot moves along the modified route, handling the teaching substrate. Based at least in part on the sensor data, positions of the plurality of stations are determined.