Wafer Critical Dimension Control via Representative Feature Metrology
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Solution Overview
Problem
In semiconductor device fabrication, there is a challenge in accurately controlling critical dimensions of features on a wafer due to the complex interactions of process control parameters, which hinders the ability to consistently achieve target values across the wafer surface.
Innovation Solution
A method and system that determine a representative feature on the wafer with a correlated critical dimension response to a specified process control parameter, allowing for adjustments to this parameter to drive the critical dimension of the representative feature to a target value, and subsequently updating the process controller to implement these adjustments during subsequent wafer processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If process control parameters are adjusted to achieve target critical dimensions, then manufacturing precision is improved, but the complexity of controlling multiple interacting parameters increases
Solution Approach 1:
The system uses on-wafer metrology measurements to automatically determine representative features and their critical dimension responses, eliminating the need for external manual analysis. The process controller self-adjusts by using the measured critical dimension response to automatically calculate and implement process parameter adjustments, making the system self-correcting and reducing operational complexity.
Solution Approach 2:
The system implements a closed-loop feedback mechanism where on-wafer metrology measurements of critical dimensions are fed back to the process controller. The controller uses this feedback information about representative features to determine adjustments to process control parameters, creating a continuous measurement-adjustment cycle that improves precision while managing complexity through automated feedback processing.
2Measurement precision
If on-wafer metrology measurements are performed to determine critical dimensions, then measurement precision is improved, but the time required for process control increases
Solution Approach 1:
The system extracts only the critical information needed for process control by identifying representative features and measuring only their critical dimensions, rather than measuring all features on the wafer. This extraction of essential measurement data maintains measurement precision for control decisions while significantly reducing the time required compared to comprehensive wafer-wide measurements.
Solution Approach 2:
The system performs preliminary identification of representative features and their correlated critical dimension responses before final process adjustments are made. By pre-establishing the relationships between process parameters and representative feature responses, the system prepares the necessary measurement framework in advance, enabling faster real-time control decisions without sacrificing measurement precision.
3Ease of operation
If representative features are used to simplify process control, then ease of operation is improved, but the reliability of controlling all features on the wafer may be reduced
Solution Approach 1:
The system applies local quality by identifying representative features at specific locations on the wafer that exhibit critical dimension responses correlated with other features in their respective areas. Each representative feature serves as a local indicator for its region, allowing simplified control operations while maintaining reliability through the correlated response relationship between representative and non-representative features within each local area.
Solution Approach 2:
The representative features serve multiple functions: they are measured for critical dimension evaluation, used to determine process parameter adjustments, and act as indicators for the quality of other features in their vicinity. This multi-functionality allows the system to maintain reliability across the entire wafer while simplifying operations through the use of a reduced set of representative measurement points.
Data Source
AI summary
A method for controlling a semiconductor fabrication process includes determining a representative feature within a given area on a wafer. The representative feature has a critical dimension (CD) response to a specified process control parameter that is correlated to a CD response to the specified process control parameter of other features within the given area on the wafer. A CD adjustment is determined for the representative feature to achieve a target CD for the representative feature. The CD response to the specified process control parameter for the representative feature and the CD adjustment for the representative feature are used to determine an adjustment to the specified process control parameter that will drive a CD of the representative feature to the target critical dimension for the representative feature. A process controller is updated to implement the adjustment to the specified process control parameter during subsequent processing of another wafer.