20240086599.SYSTEM AND METHOD FOR MODELING A SEMICONDUCTOR FABRICATION PROCESS simplified abstract (samsung electronics co., ltd.)
Contents
- 1 SYSTEM AND METHOD FOR MODELING A SEMICONDUCTOR FABRICATION PROCESS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SYSTEM AND METHOD FOR MODELING A SEMICONDUCTOR FABRICATION PROCESS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
SYSTEM AND METHOD FOR MODELING A SEMICONDUCTOR FABRICATION PROCESS
Organization Name
Inventor(s)
Moonhyun Cha of Yongin-si (KR)
Changwook Jeong of Hwaseong-si (KR)
SYSTEM AND METHOD FOR MODELING A SEMICONDUCTOR FABRICATION PROCESS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240086599 titled 'SYSTEM AND METHOD FOR MODELING A SEMICONDUCTOR FABRICATION PROCESS
Simplified Explanation
The abstract describes a system for modeling a semiconductor fabrication process using machine learning models trained on pairs of images of design patterns and physical patterns. The system generates output data defining the physical pattern and/or design pattern based on input images representing the shape of the patterns.
- Machine learning models trained on pairs of images of design patterns and physical patterns
- System generates output data defining physical and design patterns based on input images
- Utilizes at least one first processor and at least one second processor
Potential Applications
This technology could be applied in the semiconductor industry for optimizing and automating the fabrication process, improving pattern recognition, and enhancing overall efficiency in manufacturing.
Problems Solved
This technology helps in accurately predicting physical patterns based on design patterns, reducing errors in the fabrication process, and streamlining the production of semiconductor devices.
Benefits
The system offers improved accuracy in pattern recognition, increased efficiency in semiconductor fabrication, and potential cost savings through automation and optimization.
Potential Commercial Applications
The technology could be utilized in semiconductor manufacturing companies to enhance production processes, improve quality control, and increase overall productivity.
Possible Prior Art
Prior art in this field may include research on machine learning applications in semiconductor manufacturing, pattern recognition algorithms, and image processing techniques used in fabrication processes.
Unanswered Questions
How does this technology impact the overall efficiency of semiconductor fabrication processes?
This technology can significantly improve the efficiency of semiconductor fabrication processes by accurately predicting physical patterns based on design patterns, reducing errors, and streamlining production.
What are the potential cost savings associated with implementing this technology in semiconductor manufacturing?
Implementing this technology can lead to cost savings through automation, improved quality control, and optimized production processes, resulting in reduced waste and increased productivity.
Original Abstract Submitted
a system for modeling a semiconductor fabrication process includes at least one first processor and at least one second processor. the at least one first processor is configured to provide at least one machine learning (ml) model, which is trained by using a plurality of pairs of images of a design pattern sample and a physical pattern sample. the physical pattern sample is formed from the design pattern sample by using the semiconductor fabrication process. the at least one second processor is configured to provide an input image representing a shape of a design pattern and/or a physical pattern to the at least one first processor and to generate output data defining the physical pattern and/or the design pattern based on an output image received from the at least one first processor.
