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An interpretable unsupervised Bayesian network model for fault detection and diagnosis

Autor: Wei-Ting Yang, Marco S. Reis, Valeria Borodin, Michel Juge, Agnès Roussy

Publikováno v: Control Engineering Practice
Control Engineering Practice, 2022, 127, pp.105304. ⟨10.1016/j.conengprac.2022.105304⟩

International audience

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e74ee4e75af3f7447f5d9f735e8c71b
https://hal-emse.ccsd.cnrs.fr/emse-03754041

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Virtual metrology for semiconductor manufacturing: Focus on transfer learning

Autor: Rebecca Clain, Michel Juge, Valeria Borodin, Agnes Roussy

Publikováno v: CASE

Nowadays, virtual metrology models for semiconductor manufacturing aim to be scalable. A Virtual Metrology (VM) system is intended to cover a wide spectrum of production contexts. However, due to the large numbers of possible combinations of recipes,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cfdcb79d3db39c64636e2e54dff98353
https://doi.org/10.1109/case49439.2021.9551567

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A hybrid feature selection approach for virtual metrology: Application to CMP process

Autor: Agnes Roussy, Valeria Borodin, Michel Juge, Taki Eddine Korabi

Publikováno v: 2021 32nd Annual SEMI Advanced Semiconductor Manufacturing Conference (ASMC).

This paper presents a feature selection method for virtual metrology applied to a chemical mechanical planarization process in the semiconductor industry. The proposed approach is based on a filter method coupled with a wrapper method. The goal of th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::029b61d89b5387deb4b7f07afdf87620
https://doi.org/10.1109/asmc51741.2021.9435673

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A Comparative Evaluation of Deep Learning Anomaly Detection Techniques on Semiconductor Multivariate Time Series Data

Autor: Philip Tchatchoua, Mustapha Ouladsine, Michel Juge, Guillaume Graton

Publikováno v: 2021 IEEE 17th International Conference on Automation Science and Engineering (CASE)
CASE
IEEE 17th International Conference on Automation Science and Engineering (CASE)

In industrial processes, keeping equipment units in good operating conditions while reducing maintenance costs is one of the most important objectives to improve productivity. One of the ways to do so is to early detect equipment dysfunction. This ca

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d375218e0551ffd5171ec1a7f1fdcbab

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