Sequential and Comprehensive Algorithm for Fault Detection in Semiconductor Sensors
| Autor: | Suho Jeong, Tae Hyeon Kim, Jongmin Lee, Seungho Lee, Hirak Mazumdar, Euiseok Kum, Bong Geun Chung |
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| Rok vydání: | 2021 |
| Předmět: |
Technology
QH301-705.5 Semiconductor device fabrication Computer science QC1-999 Big data Fault detection and isolation statistical process control General Materials Science Voronoi diagram Biology (General) Cluster analysis QD1-999 Instrumentation Fluid Flow and Transfer Processes business.industry Physics Process Chemistry and Technology General Engineering Regression analysis Engineering (General). Civil engineering (General) Statistical process control Computer Science Applications Chemistry machine learning Key (cryptography) TA1-2040 business defect classification Algorithm |
| Zdroj: | Applied Sciences, Vol 11, Iss 10419, p 10419 (2021) Applied Sciences Volume 11 Issue 21 |
| ISSN: | 2076-3417 |
| Popis: | The semiconductor manufacturing processes have been evolved to improve the yield rate. Here, we studied a sequential and comprehensive algorithm that could be used for fault detection and classification (FDC) of the semiconductor chips. A statistical process control (SPC) method is employed for inspecting whether sensors used in the semiconductor manufacturing process become stable or not. When the sensors are individually stable, the algorithm conducts the relational inspection to identify the relationship between two sensors. The key factor here is the coefficient of determination (R2). If R2 is calculated as more than 0.7, their relationship is analyzed through the regression analysis, while the algorithm conducts the clustering analysis to the sensor pair with R2 less than 0.7. This analysis also provided the capability to determine whether the newly generated data are defective or defect-free. Therefore, this study is not only applied to the semiconductor manufacturing process but can also be to the various research fields where the big data are treated. |
| Databáze: | OpenAIRE |
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