Name
Title | ||
|---|---|---|
Multi-Feature Shuffle Algorithm for Root Cause Detection in Semiconductor Manufacturing |
Abstract | ||
|---|---|---|
The semiconductor industry has achieved complete automation in the manufacturing process where sensors collect a large number of process parameters online for fault detection and classification. Usually those data with a large number of parameters are complex and the process is multivariate, making it difficult for traditional methods to effectively perform root cause detection. In recent years, m... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/DASC-PICom-CBDCom-CyberSciTech52372.2021.00034 | 2021 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) |
Keywords | DocType | ISBN |
Semiconductor device modeling,Analytical models,Manufacturing processes,Machine learning,Semiconductor device manufacture,Feature extraction,Production facilities | Conference | 978-1-6654-2174-4 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ding Tan | 1 | 0 | 0.34 |
| Xingyu Xu | 2 | 0 | 0.34 |
| Kaixiang Yu | 3 | 0 | 0.34 |
| Sihai Zhang | 4 | 0 | 0.34 |
| Tianchi Chen | 5 | 0 | 0.34 |