Samsung electronics co., ltd. (20240332093). CRITICAL DIMENSION PREDICTION SYSTEM AND OPERATION METHOD THEREOF simplified abstract
Contents
CRITICAL DIMENSION PREDICTION SYSTEM AND OPERATION METHOD THEREOF
Organization Name
Inventor(s)
YOUNGHOON Sohn of Suwon-si (KR)
CRITICAL DIMENSION PREDICTION SYSTEM AND OPERATION METHOD THEREOF - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240332093 titled 'CRITICAL DIMENSION PREDICTION SYSTEM AND OPERATION METHOD THEREOF
Simplified Explanation: The patent application describes a system that uses a measuring device to collect data from a semiconductor chip, including multiple spectrums. This data is then used to train an artificial intelligence model to predict critical dimensions of a target layer.
- Key Features and Innovation:
- Measuring device acquires sample data from semiconductor chip - Training data selection device selects training data set based on sample data - Critical dimension predicting model generating device trains AI model to predict critical dimensions - Critical dimension predicting device predicts critical dimension of target layer using input data - Sparsity score assigned to spectrums to select training data set
- Potential Applications:
- Semiconductor manufacturing - Quality control in chip production - Process optimization in semiconductor industry
- Problems Solved:
- Accurate prediction of critical dimensions - Efficient training of AI models for semiconductor analysis
- Benefits:
- Improved accuracy in critical dimension prediction - Enhanced efficiency in semiconductor manufacturing processes
- Commercial Applications:
- "Advanced Semiconductor Critical Dimension Prediction System for Enhanced Manufacturing Efficiency"
- Prior Art:
- Researchers can explore existing patents related to AI models in semiconductor manufacturing.
- Frequently Updated Research:
- Stay updated on advancements in AI models for semiconductor analysis.
Questions about Semiconductor Critical Dimension Prediction System: 1. How does the system improve efficiency in semiconductor manufacturing processes? 2. What are the potential challenges in implementing this technology in the semiconductor industry?
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Original Abstract Submitted
a critical dimension prediction system includes a measuring device configured to acquire sample data from a sample semiconductor chip, the sample data including a plurality of spectrums, a training data selection device configured to select a training data set based on the sample data, a critical dimension predicting model generating device configured to generate a critical dimension predicting model by training an artificial intelligence model based on the training data set, and a critical dimension predicting device configured to predict a critical dimension of a target layer by inputting input data into the critical dimension predicting model, the input data including information about the target layer, where the training data selection device is further configured to assign a sparsity score to each of the plurality of spectrums and select at least one of the plurality of spectrums as the training data set based on the sparsity score.
