Process Kit Ring Alignment Using Sensor-Based Position Correction
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Solution Overview
Problem
Conventional systems face challenges in accurately positioning process kit rings in substrate processing equipment, leading to suboptimal substrate production, increased downtime, and reduced yield.
Innovation Solution
A method involving a processing device that removes an upper process kit ring from a lower one, performs position corrections based on sensor data, and then reassembles the rings, utilizing machine learning models for precise alignment without opening the processing chamber.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional positioning methods are used for process kit rings, then device complexity is reduced, but manufacturing precision deteriorates
Solution Approach 1:
The patent replaces conventional mechanical positioning systems with sensor-based detection and machine learning algorithms. Sensors capture position data of process kit rings, and ML models automatically determine optimal positioning, eliminating complex mechanical adjustment mechanisms while achieving superior positioning accuracy.
Solution Approach 2:
The system enables self-positioning of process kit rings through autonomous sensor detection and machine learning-based decision making. The process kit rings are positioned accurately without requiring complex external positioning devices or manual intervention, as the system automatically detects and corrects positioning deviations.
2Manufacturing precision
If process kit rings are not accurately positioned, then device complexity is reduced, but substrate quality deteriorates
Solution Approach 1:
The patent replaces complex mechanical positioning systems with sensor-based detection and machine learning algorithms. Sensors capture position data of process kit rings, and ML models automatically determine optimal positioning, eliminating complex mechanical adjustment mechanisms while achieving superior positioning accuracy.
Solution Approach 2:
The system implements feedback control by continuously monitoring the position of process kit rings using sensors and automatically adjusting positioning based on machine learning model predictions. This closed-loop feedback mechanism ensures consistent substrate quality without requiring overly complex positioning hardware.
3Productivity
If manual positioning methods are used, then ease of operation is maintained, but productivity deteriorates
Solution Approach 1:
The system enables self-positioning of process kit rings through autonomous sensor detection and machine learning-based decision making. The process kit rings are positioned accurately without requiring complex external positioning devices or manual intervention, as the system automatically detects and corrects positioning deviations.
Solution Approach 2:
The patent replaces complex mechanical positioning systems with sensor-based detection and machine learning algorithms. Sensors capture position data of process kit rings, and ML models automatically determine optimal positioning, eliminating complex mechanical adjustment mechanisms while achieving superior positioning accuracy.
Data Source
AI summary
A method includes causing an upper process kit ring to be removed from a lower process kit ring. The method further includes, responsive to causing the upper process kit ring to be removed from the lower process kit ring, causing, based on sensor data, a first position correction associated with the lower process kit ring. The method further includes, responsive to the first position correction, causing the upper process kit ring to be disposed on the lower process kit ring.


