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Deep multistage multi-task learning for quality prediction of multistage manufacturing systems
  • Quality

Deep multistage multi-task learning for quality prediction of multistage manufacturing systems

Publication:
Journal of Quality Technology
Date:
November 2021
Issue:
Volume 53 Issue 5
Pages:
pp. 526-544
Author(s):
Yan, Hao, Sergin, Nurettin Dorukhan, Brenneman, William A., Lange, Stephen Joseph, Ba, Shan

Abstract

In multistage manufacturing systems, modeling multiple quality indices based on the process sensing variables is important. However, the classic modeling technique predicts each quality variable one at a time, which fails to consider the correlation within or between stages. We propose a deep multistage multi-task learning framework to jointly predict all output sensing variables in a unified end-to-end learning framework according to the sequential system architecture in the MMS. Our numerical studies and real case study have shown that the new model has a superior performance compared to many benchmark methods as well as great interpretability through developed variable selection techniques.

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