Substrate Shape Prediction Feedback for Precise Process Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The accuracy of shape prediction using trained models in substrate processing, such as etching or film formation on semiconductor wafers, often differs from that of traditional shape simulations, leading to potential manufacturing defects and reduced yield.
Innovation Solution
Integrate evaluation and improvement of trained model prediction accuracy by optimizing processing parameters like gas flow rates, voltage, and pressure, using a retrained model to enhance control of substrate processing apparatuses, and incorporate additional physical effects like temperature and electric fields.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a trained model is used for shape prediction in substrate processing, then prediction speed is improved, but prediction accuracy deteriorates compared to shape simulation
Solution Approach 1:
The patent introduces a shape simulation system as an intermediary component that works in conjunction with the trained model. The simulation calculates correction values based on the difference between simulated and actual shapes, which are then used to improve the trained model's prediction accuracy. This intermediary simulation component enables the fast trained model to achieve accuracy comparable to full simulations.
Solution Approach 2:
The system implements a feedback mechanism where the shape simulation results are compared with actual measured shapes from substrate processing, and the difference (error) is fed back to correct and improve the trained model's predictions. This feedback loop allows the trained model to maintain high speed while achieving accurate predictions through continuous correction based on simulation data.
2Manufacturing precision
If processing parameters are adjusted to optimize substrate processing, then manufacturing precision is improved, but device complexity increases due to multiple parameters to control
Solution Approach 1:
The patent uses shape simulation to create a virtual copy or model of the substrate processing outcome before actual processing occurs. This simulated shape prediction allows operators to evaluate different parameter combinations in a virtual environment, selecting optimal parameters without having to physically test multiple combinations, thereby reducing the complexity of parameter control while maintaining high manufacturing precision.
Solution Approach 2:
The system performs preliminary shape simulation and parameter optimization before actual substrate processing. By calculating predicted shapes and adjusting parameters in advance using the trained model and simulation, the system determines optimal processing conditions beforehand, simplifying the actual processing operation while ensuring high manufacturing precision.
Data Source
AI summary
Using a simulation model that simulates substrate processing using a plurality of parameters related to a condition of the substrate processing, or a trained model that outputs a predicted shape of a substrate after processing according to inputs of the plurality of parameters and an initial shape of the substrate, the plurality of parameters are adjusted such that the predicted shape becomes a specific shape. A predicted shape is acquired by simulating the substrate processing by the simulation model using the plurality of parameters after the adjustment and a specific initial shape of the substrate and using the trained model according to the plurality of parameters after the adjustment and the specific initial shape. An error between the predicted shape acquired by the simulation model and the predicted shape acquired using the trained model is calculated. Accuracy of the prediction using the trained model is determined based on the error.