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

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

This research proposes an application of generative adversarial networks (GANs) to solve the class imbalance problem in the fault detection and classification study of a plasma etching process. Small changes in the equipment part condition of the plasma equipment may cause an equipment fault, result...

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Bibliographic Details
Main Authors: Jeong Eun Choi, Da Hoon Seol, Chan Young Kim, Sang Jeen Hong
Format: Article
Language:English
Published: MDPI AG 2023-02-01
Series:Sensors
Subjects:
fault detection
generative adversarial networks
machine learning
optical emission spectroscopy
plasma etch
Online Access:https://www.mdpi.com/1424-8220/23/4/1889

Internet

https://www.mdpi.com/1424-8220/23/4/1889

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