RTP Chamber Cleanliness Prediction for In-Situ Outgassing Removal
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Solution Overview
Problem
Material outgassing in semiconductor processing chambers leads to deposits on interior surfaces, causing temperature sensor mis-readings and process control issues, necessitating frequent manual cleaning and requalification, which is time-consuming and requires downtime.
Innovation Solution
Implement an automated chamber monitoring and cleaning process using AI or ML models to predict chamber cleanliness and trigger self-cleaning operations when deposits exceed a threshold, allowing for waferless cleaning without opening the chamber.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual wet cleaning is performed to remove deposits from chamber surfaces, then chamber cleanliness is improved, but chamber downtime increases and requalification is required
Solution Approach 1:
The chamber performs self-cleaning through automated in-situ cleaning processes that remove deposits without requiring manual intervention or chamber opening. The system monitors its own condition and executes cleaning cycles autonomously, eliminating the need for external service and minimizing downtime.
Solution Approach 2:
The system performs preliminary cleaning actions before deposits reach critical levels that would require manual intervention. By continuously monitoring chamber conditions and executing preventive cleaning, the system avoids the need for time-consuming manual wet cleaning and requalification processes.
2Manufacturing precision
If daily test wafer monitoring is used to trigger tool down for preventative maintenance, then chamber cleanliness can be maintained, but productivity decreases due to frequent tool downtime
Solution Approach 1:
The patent replaces mechanical test wafer monitoring with optical sensing systems that continuously monitor chamber conditions without requiring physical test substrates. This substitution eliminates the need to take the tool offline for testing while maintaining monitoring capability.
Solution Approach 2:
The monitoring system operates continuously during normal production runs rather than requiring periodic tool shutdowns for testing. This continuous monitoring approach maintains productivity while still detecting when cleaning is needed through real-time analysis of chamber conditions.
3Power
If temperature sensors are used to monitor chamber temperature, then process control is enabled, but measurement precision deteriorates due to surface contamination on sensors
Solution Approach 1:
The temperature sensors perform self-cleaning through automated cleaning processes that remove contamination from sensor surfaces. This self-service capability maintains measurement precision without requiring manual sensor cleaning or replacement, allowing continuous accurate temperature monitoring for process control.
Solution Approach 2:
The system introduces an intermediary cleaning process between the contaminated sensor and the measurement function. By inserting a cleaning step that removes deposits from the sensor surface, the system restores the sensor's measurement capability without requiring manual intervention or sensor replacement.
Data Source
AI summary
Embodiments disclosed herein include a method of monitoring a condition of a chamber. In an embodiment, the method comprises processing a substrate in the chamber, providing substrate history and chamber data to a model of the chamber, where the model of the chamber is configured to predict a chamber cleanliness, comparing the predicted chamber cleanliness against a performance limit, and flagging the chamber for preventive maintenance (PM) when the predicted chamber cleanliness is above the performance limit.