Hierarchical Transfer Learning for Cycle Time Forecasting for Semiconductor Wafer Lot under Different Work in Process Levels

Hierarchical Transfer Learning for Cycle Time Forecasting for Semiconductor Wafer Lot under Different Work in Process Levels

The accurate cycle time (CT) prediction of the wafer fabrication remains a tough task, as the system level of work in process (WIP) is fluctuant. Aiming to construct one unified CT forecasting model under dynamic WIP levels, this paper proposes a transfer learning method for finetuning the predicted...

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Bibliographic Details
Main Authors: Junliang Wang, Pengjie Gao, Zhe Li, Wei Bai
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Mathematics
Subjects:
wafer fabrication
cycle time
time series prediction
work in process
convolutional neural network
hierarchical optimization
Online Access:https://www.mdpi.com/2227-7390/9/17/2039

Internet

https://www.mdpi.com/2227-7390/9/17/2039

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