Samsung electronics co., ltd. (20240135523). SEMICONDUCTOR YIELD PREDICTION METHOD AND APPARATUS simplified abstract
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 20240135523 titled 'SEMICONDUCTOR YIELD PREDICTION METHOD AND APPARATUS
Simplified Explanation
The patent application describes a method of predicting semiconductor yield by analyzing wafer level data, generating virtual chips, mapping test results, computing defect rates, and calculating a defect index of the equipment.
- Analyzing wafer level data to predict semiconductor yield
- Generating virtual chips based on wafer level data
- Mapping test results to virtual chips
- Computing defect rates based on test results
- Calculating a defect index of the equipment
Potential Applications
This technology can be applied in semiconductor manufacturing to improve yield prediction and quality control processes.
Problems Solved
This technology helps in identifying defects in semiconductor chips early in the manufacturing process, allowing for timely corrective actions to be taken.
Benefits
The method can lead to increased efficiency in semiconductor manufacturing, reduced waste, and improved overall product quality.
Potential Commercial Applications
One potential commercial application of this technology could be in the semiconductor industry for optimizing production processes and reducing costs.
Possible Prior Art
One possible prior art could be similar methods used in the semiconductor industry for yield prediction and quality control, but this specific combination of steps may be novel.
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, leaving the reader to wonder about the potential advantages or limitations of this approach.
Are there any specific industries or sectors where this technology would be most beneficial?
The article does not mention any specific industries or sectors where this technology could have the most significant impact, leaving room for exploration of potential applications beyond semiconductor manufacturing.
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.