Generative Adversarial Network-Based Fault Detection in Semiconductor Equipment with Class-Imbalanced Data.

Choi, Jeong Eun; Seol, Da Hoon; Kim, Chan Young; Hong, Sang Jeen

Choi, Jeong Eun; Seol, Da Hoon; Kim, Chan Young; Hong, Sang Jeen.

Afiliação

Choi JE; Department of Electronics Engineering, Myongji University, 116 Myongji-ro, Yongin-si 17058, Gyeonggi-do, Republic of Korea.
Seol DH; Department of Electronics Engineering, Myongji University, 116 Myongji-ro, Yongin-si 17058, Gyeonggi-do, Republic of Korea.
Kim CY; Department of Electronics Engineering, Myongji University, 116 Myongji-ro, Yongin-si 17058, Gyeonggi-do, Republic of Korea.
Hong SJ; Department of Electronics Engineering, Myongji University, 116 Myongji-ro, Yongin-si 17058, Gyeonggi-do, Republic of Korea.

Sensors (Basel) ; 23(4)2023 Feb 08.

Article em En | MEDLINE | ID: mdl-36850488

Palavras-chave

fault detection; generative adversarial networks; machine learning; optical emission spectroscopy; plasma etch

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Sensors (Basel) Ano de publicação: 2023 Tipo de documento: Article

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