Machine Vision Robot Teaching for Vacuum Substrate Handling
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Solution Overview
Problem
Conventional methods for teaching substrate holding locations in substrate processing equipment require sensors that disrupt vacuum environments, necessitate changes to customer equipment, and are not suitable for high temperatures, often leading to human error and variability.
Innovation Solution
An automatic teach apparatus using software and hardware with machine vision systems and teach fixtures to automate the teaching process, minimizing human error and setup time, and verifying robotic end effector leveling relative to substrate holding stations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If sensors are placed within the substrate processing equipment to detect substrate holding locations, then teaching precision is improved, but vacuum environment is disrupted
Solution Approach 1:
The patent introduces an intermediary optical system consisting of external cameras and reflective targets. The cameras are positioned outside the vacuum chamber and capture images of reflective targets placed on substrate holding stations through the chamber window. This intermediary optical path allows teaching without placing sensors inside the vacuum environment, thus resolving the contradiction between measurement precision and vacuum environment protection.
Solution Approach 2:
The patent replaces mechanical sensors that would physically contact or be placed within the vacuum chamber with an optical measurement system. The optical system uses cameras and reflective targets to determine substrate holding locations through non-contact image processing, eliminating the need for mechanical sensors inside the vacuum environment while maintaining teaching precision.
2Device complexity
If manual teaching methods are used to program substrate holding locations, then equipment complexity is reduced, but human error and variability increase
Solution Approach 1:
The patent implements an automated teaching system where the robotic end effector autonomously determines substrate holding locations by capturing images with onboard cameras and processing the images to calculate position data. The system self-calibrates by detecting reflective targets and automatically computing transformation matrices, eliminating manual intervention and thereby reducing human error while maintaining reasonable system complexity through software-based solutions.
Solution Approach 2:
The patent incorporates feedback mechanisms where the robotic end effector uses onboard cameras to capture images of reflective targets, processes these images to determine actual positions, and automatically adjusts its coordinate system accordingly. This closed-loop feedback ensures consistent teaching accuracy without requiring complex manual procedures, as the system self-corrects based on actual measured positions.
3Loss of time
If conventional teaching methods are used, then setup time is reduced, but positioning precision deteriorates
Solution Approach 1:
The patent implements preliminary action by pre-placing reflective targets on substrate holding stations before the teaching process begins. The robotic end effector is pre-equipped with onboard cameras and image processing capabilities. This preliminary preparation enables rapid automated teaching without requiring time-consuming manual measurements or sensor calibrations during the actual teaching process, thus reducing setup time while ensuring high positioning precision through automated image-based measurement.
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
The solution decreases setup time and minimizes human error while ensuring precise positioning of substrates, compatible with both atmospheric and vacuum environments.
Implementation Method 1
an machine vision system including at least one fixed imaging sensor and at least one movable imaging sensor
Data Source
AI summary
An automatic teaching system for a substrate processing apparatus, the automatic teaching system comprising a frame having a workpiece load station with a predetermined load station reference location, a robot transport mounted to the frame and having a movable transport arm with an end effector having a predetermined end effector reference location, and a drive section driving the movable transport arm in at least one degree of freedom motion relative to the frame, a machine vision system including both at least one fixed imaging sensor and at least one movable imaging sensor removably connected to the frame and configured to image at least one target of the machine vision system, a load jig disposed for removable engagement with the workpiece load station, with both the at least one fixed imaging sensor and the at least one movable imaging sensor mounted to the load jig, the fixed imaging sensor.