Topography Simulator Evaluation Apparatus for Prediction Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The accuracy of topography prediction by existing topography simulators decreases when a new substrate with a significantly different topography is used, as the simulation parameters derived from previous substrates do not effectively predict the new substrate's processed topography, necessitating an evaluation method to assess the prediction reliability.
Innovation Solution
An evaluation apparatus and method that calculates simulation parameters to align the predicted topography of a new unprocessed substrate with that of a processed substrate, using range information to evaluate the prediction accuracy by comparing the topography data within predetermined ranges, thereby determining if the prediction is high or low accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If simulation parameters are derived from previous substrates to predict topography, then prediction capability is improved, but prediction accuracy deteriorates when new substrates with significantly different topography are used
Solution Approach 1:
The evaluation apparatus performs preliminary evaluation of prediction accuracy before final topography prediction is accepted. By预先 calculating simulation parameters from multiple pairs of unprocessed and processed substrate topography data, and establishing reference ranges beforehand, the system can assess whether new substrate predictions will be accurate before relying on them, thus resolving the contradiction between maintaining prediction capability and ensuring prediction accuracy.
Solution Approach 2:
The system implements a feedback mechanism where prediction accuracy is continuously evaluated by comparing simulated topography against actual measured topography data. The evaluation result feeds back into adjusting simulation parameters and refining reference ranges, allowing the system to adapt to new substrate types while maintaining accuracy. This closed-loop feedback resolves the contradiction by enabling the system to learn from previous predictions and improve future accuracy.
2Reliability
If simulation parameters are calculated to match processed substrate topography, then prediction reliability is improved, but the complexity of the evaluation process increases
Solution Approach 1:
The evaluation process is segmented into distinct modular steps: (1) acquiring multiple pairs of unprocessed and processed substrate topography data, (2) calculating simulation parameters from each pair, (3) determining reference ranges from the calculated parameters, (4) evaluating new predictions by comparing against reference ranges. This segmentation makes the complex evaluation process more manageable and systematic while maintaining high prediction reliability through comprehensive parameter matching.
3Measurement precision
If range information is used to evaluate prediction accuracy, then assessment reliability is improved, but the computational requirements and processing time increase
Solution Approach 1:
The system uses partial action by evaluating only the critical parameters that fall within predetermined reference ranges, rather than performing exhaustive analysis of all possible topography parameters. This selective evaluation approach maintains high assessment reliability for the most important prediction accuracy indicators while significantly reducing overall processing time and computational requirements.
Data Source
AI summary
An evaluation apparatus includes a processor that performs operations including reading a simulation parameter of a topography simulator and first range information or second range information that are associated with each other, the simulation parameter being calculated to cause the topography simulator output topography information of a processed target object that is to be obtained by processing the unprocessed target object under a predetermined processing condition, providing topography information of a new unprocessed target object and the simulation parameter to the topography simulator to cause the topography simulator to predict topography information of a new processed target object that is processed under the predetermined processing condition, and outputting a result of comparing the topography information of the new unprocessed target object with the first range information or a result of comparing the topography information of the new processed target object with the second range information.