Autocalibration Wafer Positioning for Wafer-Handling Robot Teach
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Solution Overview
Problem
Current semiconductor processing tools face challenges in accurately calibrating wafer-handling robots due to variance in relative positioning between the robot's end effector and semiconductor wafers, which requires manual or semi-automated teaching processes that are time-consuming and prone to errors.
Innovation Solution
The implementation of an autocalibration wafer system equipped with downward-facing imaging sensors and a controller, which assists in calibrating the wafer-handling robot by determining the offset between the wafer and the wafer support, allowing for automated teaching and correction of wafer placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual or semi-automated teaching processes are used to calibrate wafer-handling robots, then positioning accuracy can be achieved, but the calibration process becomes time-consuming and prone to errors
Solution Approach 1:
The autocalibration wafer system enables the wafer-handling robot to perform self-calibration automatically. The robot picks up the autocalibration wafer using its end effector, and through automated imaging and coordinate extraction processes, the system determines offset values without human intervention. This self-service approach eliminates time-consuming manual teaching while maintaining high positioning accuracy through automated feedback mechanisms.
Solution Approach 2:
The system performs preliminary calibration actions by placing fiducial markers on the autocalibration wafer before the actual wafer handling process. These pre-positioned fiducials allow the imaging system to capture reference coordinates in advance, enabling the robot to calculate and compensate for positioning offsets before production wafers are processed, thereby reducing calibration time while ensuring accuracy.
2Measurement precision
If manual teaching processes are used for robot calibration, then positioning accuracy can be achieved, but the process becomes complex and requires human intervention
Solution Approach 1:
The system replaces manual mechanical teaching operations with an automated optical-mechanical system. Instead of human operators manually moving the robot to teach positions, the system uses imaging sensors to capture fiducial markers, automatically extracts coordinates through image processing, and calculates offset values. This substitution of manual mechanical operations with automated sensing and computation simplifies the calibration process while maintaining high positioning precision.
Solution Approach 2:
The autocalibration wafer with fiducial markers serves as an intermediary object that facilitates automated calibration. This intermediary contains precisely positioned fiducials that the imaging system can detect, allowing the robot to determine offset values without direct human manipulation. The intermediary wafer bridges the gap between the robot's end effector and the target wafer position, enabling automated measurement and calibration.
3Device complexity
If variance in relative positioning between end effector and wafer is not corrected, then the calibration process is simplified, but wafer placement accuracy deteriorates
Solution Approach 1:
The system implements a feedback mechanism where the imaging sensors capture the actual position of fiducial markers on the autocalibration wafer, the controller extracts coordinates and calculates offset values, and these offset values are then used to correct the robot's positioning. This closed-loop feedback ensures that variance in relative positioning between the end effector and wafer is measured and compensated, maintaining high manufacturing precision while automating the calibration process.
Data Source
AI summary
Systems and techniques for determining and using multiple types of offsets for providing wafers to a wafer support of a wafer station of a semiconductor processing tool are disclosed; such techniques and systems may use an autocalibration wafer that may include a plurality of sensors, including a plurality of edge-located imaging sensors that may be used to image fiducials associated with two different structures located in a selected wafer station.