18486350. SEMICONDUCTOR YIELD PREDICTION METHOD AND APPARATUS simplified abstract (SAMSUNG ELECTRONICS CO., LTD.)
Contents
- 1 SEMICONDUCTOR YIELD PREDICTION METHOD AND APPARATUS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SEMICONDUCTOR YIELD PREDICTION METHOD AND APPARATUS - 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 Unanswered Questions
- 1.11 Original Abstract Submitted
SEMICONDUCTOR YIELD PREDICTION METHOD AND APPARATUS
Organization Name
Inventor(s)
Sungwook Hwang of Suwon-si (KR)
SEMICONDUCTOR YIELD PREDICTION METHOD AND APPARATUS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18486350 titled 'SEMICONDUCTOR YIELD PREDICTION METHOD AND APPARATUS
Simplified Explanation
The patent application describes a method of predicting semiconductor yield by analyzing wafer level data and generating virtual chips based on that data.
- Receiving wafer level data from multiple wafers
- Generating virtual chips corresponding to the wafers based on the data
- Mapping test results from the wafers to the virtual chips
- Computing defect rates of the virtual chips based on the mapping results
- Computing a defect index of the equipment based on the defect rate
Potential Applications
This technology could be applied in semiconductor manufacturing to improve yield prediction and quality control processes.
Problems Solved
This technology helps in predicting semiconductor yield more accurately, identifying defects, and improving overall manufacturing efficiency.
Benefits
The method can lead to reduced waste, improved product quality, and increased overall yield in semiconductor manufacturing processes.
Potential Commercial Applications
This technology could be utilized by semiconductor manufacturers to optimize production processes and enhance product quality.
Possible Prior Art
One possible prior art could be the use of statistical analysis in semiconductor manufacturing to predict yield and identify defects.
Unanswered Questions
How does this method compare to traditional yield prediction techniques in terms of accuracy and efficiency?
The article does not provide a direct comparison between this method and traditional techniques.
What are the potential limitations or challenges in implementing this technology in a real-world manufacturing environment?
The article does not address any potential limitations or challenges that may arise during the implementation of this technology.
Original Abstract Submitted
A method of predicting a semiconductor yield includes receiving wafer level data generated by measuring a plurality of wafers, generating a plurality of virtual chips corresponding to the plurality of wafers based on the wafer level data, mapping a test result of the plurality of wafers to the plurality of virtual chips, computing a defect rate of the plurality of virtual chips according to defects based on a result of the mapping, and computing a defect index of the equipment based on the defect rate.
