Sample Shot Region Selection for Overlay Error Prediction
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Solution Overview
Problem
Current global alignment methods in exposure apparatuses require actual measurement to confirm the effect of parameter adjustments, which is inefficient and lacks real-time prediction capabilities for overlay errors.
Innovation Solution
An information processing apparatus that uses a first regression model to determine sample shot regions on a substrate and displays their information on a user interface, allowing for the redetermination of these regions using a second regression model, enabling the user to visualize and adjust parameters without actual measurement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If actual measurement is performed to confirm the effect of parameter adjustments, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent creates a virtual copy of the measurement process by calculating predicted overlay errors using regression models. Instead of performing actual physical measurements to confirm parameter adjustments, the system computes predicted values that replicate the measurement outcome, thereby saving time while maintaining precision.
Solution Approach 2:
The system performs preliminary calculations of predicted overlay errors before actual measurement is needed. By pre-computing the effects of parameter adjustments using regression models, the measurement process is accelerated since the predictions are already available when needed for decision-making.
2Manufacturing precision
If the number of sample shot regions is increased to improve alignment accuracy, then manufacturing precision is improved, but productivity deteriorates
Solution Approach 1:
The patent changes the parameter being measured from actual overlay errors to predicted overlay errors calculated via regression models. This parameter transformation allows the system to evaluate alignment accuracy using computational predictions rather than requiring extensive actual measurements, thereby maintaining precision while improving throughput.
Solution Approach 2:
The patent replaces the mechanical measurement system with a computational prediction system. Instead of using physical measurement equipment to assess alignment accuracy for numerous sample regions, the system uses regression-based calculations to predict overlay errors, substituting mechanical measurement with mathematical computation.
3Manufacturing precision
If high-order components are included in the regression model to improve prediction accuracy, then manufacturing precision is improved, but device complexity increases
Solution Approach 1:
The patent applies partial action by selectively including only necessary high-order components in the regression model rather than all possible terms. The system determines an appropriate degree for the regression model, incorporating sufficient complexity to achieve accurate predictions while avoiding unnecessary complexity that would increase computational burden and model difficulty.
Data Source
AI summary
An information processing apparatus includes a processor configured to determine, using a first regression model formed by a plurality of terms, a plurality of sample shot regions from a plurality of shot regions on a substrate, and a display controller configured to perform display control so that information of the plurality of sample shot regions determined by the processor is displayed on a user interface screen. The processor is configured to redetermine a plurality of sample shot regions using a second regression model formed by some terms of the plurality of terms, and the display controller is configured to update display of the user interface screen so that information of the plurality of sample shot regions redetermined by the processor is displayed on the user interface screen.