CMP Residue Detection via Machine Learning Wafer Image Analysis
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Solution Overview
Problem
The existing chemical mechanical polishing (CMP) processes face inefficiencies in determining customized additional CMP conditions for semiconductor wafers with residues, leading to inadequate polishing and reduced productivity due to manual inspection and one-size-fits-all process settings.
Innovation Solution
A chemical mechanical polishing apparatus equipped with an additional CMP process condition generator that includes a wafer image acquiring unit, image converter, residue type determining unit, and machine learning unit to automatically assess residue types and thickness, generating customized CMP conditions for each wafer based on acquired data and machine learning models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection by engineer is used to determine additional CMP conditions, then experience-based judgment can be applied, but productivity deteriorates due to time-consuming one-by-one checking
Solution Approach 1:
The patent replaces the manual mechanical inspection process with an automated optical imaging system. A camera captures wafer images, and image processing algorithms automatically analyze residue presence and characteristics, eliminating the need for manual engineer inspection while maintaining detection accuracy.
Solution Approach 2:
The system enables self-service by allowing the wafer inspection and additional CMP condition determination to be performed automatically without human intervention. The image processing unit and additional CMP process condition generator work autonomously to identify residues and determine appropriate rework conditions.
2Ease of manufacture
If uniform additional CMP process condition is applied to all wafers with residues, then process simplicity is maintained, but polishing accuracy deteriorates due to insufficient or excessive polishing for different residue states
Solution Approach 1:
The patent applies local quality by determining different additional CMP process conditions for different wafers based on their specific residue characteristics. The system analyzes each wafer's image to identify residue presence, location, and amount, then generates customized rework conditions tailored to each wafer's needs rather than applying a uniform approach.
Solution Approach 2:
The system introduces dynamics by making the additional CMP process conditions adaptive and variable rather than static and uniform. The additional CMP process condition generator dynamically adjusts polishing parameters based on real-time image analysis results, allowing the process to respond to varying residue states across different wafers.
3Ease of operation
If residue image alone is used to determine additional CMP amount, then measurement simplicity is maintained, but polishing accuracy deteriorates due to inability to determine accurate required amount
Solution Approach 1:
The patent adds another dimension to residue assessment by incorporating both image-based visual analysis and thickness measurement data. The system processes not only the visual appearance of residues from the camera image but also integrates thickness information to comprehensively determine the required additional polishing amount.
Solution Approach 2:
The patent introduces an intermediary processing layer that bridges simple image capture and accurate polishing amount determination. The image processing unit acts as an intermediary that extracts detailed residue characteristics from images, and the additional CMP process condition generator serves as another intermediary that translates these characteristics into precise polishing parameters.
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
This solution enables automatic determination and customized additional CMP processes for each wafer, minimizing over-polishing and enhancing productivity by accurately addressing varying residue states, thereby improving the precision and efficiency of the CMP process.
Implementation Method 1
a wafer macro image captured by a camera after the CMP process is performed on the wafer
Implementation Method 2
an image converter which converts the wafer macro image acquired by the wafer image acquiring unit into digital data to deduce an intensity value for each of a plurality of partitions of the wafer macro image
Implementation Method 3
a surface of a semiconductor wafer which is required to be planarized is placed to be close to the polishing pad surface to process a target surface of the semiconductor wafer by a chemical action by the slurry and a physical action by a high speed rotate
Implementation Method 4
process a target surface of the semiconductor wafer by a chemical action by the slurry and a physical action by a high speed rotate
Data Source
AI summary
A chemical mechanical polishing apparatus according to an example embodiment includes a polishing platen; a polishing pad which is located on the polishing platen and includes a polishing surface; a slurry supplier configured to supply a slurry to the polishing pad; a polishing head which is located above the polishing pad and configured to mount a wafer thereon; and an additional CMP process condition generator which generates an additional chemical mechanical polishing (CMP) process condition according to a type of residue when there is a residue on a wafer after a CMP process is performed on the wafer.