Deep multistage multi-task learning for quality prediction of multistage manufacturing systems-Reference-Cited by-同舟云学术

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

Published:2021-04-20 Issue:5 Volume:53 Page:526-544
ISSN:0022-4065
Container-title:Journal of Quality Technology
language:en
Short-container-title:Journal of Quality Technology

Author:

Yan Hao¹^ORCID,Sergin Nurettin Dorukhan¹,Brenneman William A.²,Lange Stephen Joseph²,Ba Shan²

Affiliation:

1. The School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, Arizona

2. Procter and Gamble Company, Cincinnati, Ohio

Funder

Division of Civil, Mechanical and Manufacturing Innovation

Division of Mathematical Sciences

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management,Safety, Risk, Reliability and Quality

Link

https://www.tandfonline.com/doi/pdf/10.1080/00224065.2021.1903822

Reference53 articles.

1. State Space Modeling of Variation Propagation in Multistation Machining Processes Considering Machining-Induced Variations

2. Visualizing the effects of predictor variables in black box supervised learning models

3. Diagnosis of Multiple Fixture Faults in Panel Assembly

4. Bak Ir, B. İ. Batmaz, F. Güntürkün, İ. İpekçi, G. Köksal, and N. Özdemirel. 2006. Defect cause modeling with decision tree and regression analysis. World Academy of Science, Engineering and Technology 24:1–4.

5. Large-Scale Machine Learning with Stochastic Gradient Descent

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