18498315. METHOD AND SYSTEM FOR AUGMENTING DATA BY SYNTHESIZING MEASUREMENT DATA AND SIMULATION DATA simplified abstract (Samsung Electronics Co., Ltd.)
Contents
METHOD AND SYSTEM FOR AUGMENTING DATA BY SYNTHESIZING MEASUREMENT DATA AND SIMULATION DATA
Organization Name
Inventor(s)
Bogyeong Kang of Suwon-si (KR)
Jaemyung Choe of Suwon-si (KR)
METHOD AND SYSTEM FOR AUGMENTING DATA BY SYNTHESIZING MEASUREMENT DATA AND SIMULATION DATA - A simplified explanation of the abstract
This abstract first appeared for US patent application 18498315 titled 'METHOD AND SYSTEM FOR AUGMENTING DATA BY SYNTHESIZING MEASUREMENT DATA AND SIMULATION DATA
The method described in the abstract involves augmenting training data for a semiconductor process model by synthesizing noise information and simulation data.
- Obtaining simulation input and output data sets, as well as measurement data sets.
- Extracting reference noise information from the measurement data set.
- Extracting distribution information from the simulation output data set.
- Generating a noise simulation data set based on the distribution information.
- Synthesizing the simulation input data set, noise simulation data set, and measurement data set to create a synthesized data set.
Potential Applications: - Improving the accuracy of semiconductor process modeling. - Enhancing the training data for machine learning algorithms in semiconductor manufacturing.
Problems Solved: - Addressing the challenge of limited training data for semiconductor process modeling. - Improving the robustness and reliability of simulation models in semiconductor manufacturing.
Benefits: - Increased accuracy in predicting semiconductor process outcomes. - Enhanced efficiency in training machine learning models for semiconductor manufacturing processes.
Commercial Applications: Title: "Enhanced Semiconductor Process Modeling through Data Augmentation" This technology could be utilized in the semiconductor industry to optimize manufacturing processes, improve product quality, and reduce production costs.
Questions about the technology: 1. How does this method improve the accuracy of semiconductor process modeling? 2. What are the potential implications of using synthesized data in semiconductor manufacturing processes?
Frequently Updated Research: Stay updated on advancements in semiconductor process modeling and data augmentation techniques to ensure the most effective implementation of this technology.
Original Abstract Submitted
A method of augmenting training data for a semiconductor process modeling includes obtaining a simulation input data set and a measurement data set, obtaining a simulation output data set generated based on performing simulation based on the simulation input data set, extracting reference noise information associated with the measurement data set from the measurement data set, extracting distribution information associated with each simulation case included in the simulation output data set based on synthesizing the reference noise information and the simulation output data set, generating a noise simulation data set based on sampling data based on the distribution information, and generating a synthesized data set based on synthesizing the simulation input data set, the noise simulation data set, and the measurement data set.
