Processing Chamber Cleaning Based on Deposition Thickness
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Solution Overview
Problem
Conventional fixed cleaning operations in substrate processing chambers often result in over-cleaning or under-cleaning, leading to contamination, equipment damage, and non-uniformity in semiconductor substrates due to inconsistent deposition residue thickness across processing areas.
Innovation Solution
A method that identifies deposition thickness property data to determine variable cleaning operation parameters using a trained machine learning model, optimizing cleaning time and intensity based on actual deposition residue levels in each processing area.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If fixed cleaning operations are used in substrate processing chambers, then cleaning operations can be performed with standardized parameters, but over-cleaning or under-cleaning occurs leading to contamination and equipment damage
Solution Approach 1:
The cleaning operation parameters are made dynamic by adjusting cleaning time and intensity based on real-time deposition thickness measurements. The system transitions from fixed standardized parameters to variable parameters that adapt to actual residue levels, preventing both over-cleaning and under-cleaning while maintaining reliability.
Solution Approach 2:
The invention changes the parameters of cleaning operations from fixed values to variable values based on deposition thickness. By modifying cleaning time and intensity parameters according to measured residue levels, the system achieves both customization for different conditions and standardized measurement procedures.
2Ease of operation
If fixed cleaning operations are used, then operational simplicity is maintained, but contamination and equipment damage occur due to inconsistent deposition residue thickness
Solution Approach 1:
The system implements feedback by measuring deposition thickness with sensors and using this information to adjust cleaning parameters. The measurement result feeds back to the cleaning control system, which automatically modifies cleaning time and intensity to match actual residue levels, eliminating contamination while maintaining operational simplicity.
Solution Approach 2:
The cleaning system performs self-service by automatically determining appropriate cleaning parameters based on its own measurements of deposition thickness. The system monitors its own chamber conditions and adjusts cleaning operations accordingly, reducing the need for external intervention while preventing harmful effects.
3Stability of the object's composition
If uniform cleaning parameters are applied across all processing areas, then operational consistency is achieved, but non-uniform substrate quality results due to varying deposition residue levels
Solution Approach 1:
The invention applies local quality by tailoring cleaning parameters to specific locations within the processing chamber. Different processing areas receive customized cleaning based on their individual deposition thickness measurements, ensuring each area is cleaned appropriately for its specific residue level while maintaining overall process consistency through standardized measurement and control procedures.
Data Source
AI summary
A method includes identifying deposition thickness property data associated with an amount of material deposited via one or more substrate processing operations of a process recipe performed in a processing chamber. The method further includes determining, based on the deposition thickness property data and a variable clean time relationship of the process recipe, cleaning operation parameters. The method further includes causing, based on the cleaning operation parameters, a cleaning operation in the processing chamber.