Multiple time-series convolutional neural network for fault detection and diagnosis and empirical study in semiconductor manufacturing
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DOI: 10.1007/s10845-020-01591-0
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References listed on IDEAS
- Ercan Oztemel & Samet Gursev, 2020. "Literature review of Industry 4.0 and related technologies," Journal of Intelligent Manufacturing, Springer, vol. 31(1), pages 127-182, January.
- Zhiwen Huang & Jianmin Zhu & Jingtao Lei & Xiaoru Li & Fengqing Tian, 2020. "Tool wear predicting based on multi-domain feature fusion by deep convolutional neural network in milling operations," Journal of Intelligent Manufacturing, Springer, vol. 31(4), pages 953-966, April.
- Weili Cai & Wenjuan Zhang & Xiaofeng Hu & Yingchao Liu, 2020. "A hybrid information model based on long short-term memory network for tool condition monitoring," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1497-1510, August.
- Xiang Li & Wei Zhang & Qian Ding & Jian-Qiao Sun, 2020. "Intelligent rotating machinery fault diagnosis based on deep learning using data augmentation," Journal of Intelligent Manufacturing, Springer, vol. 31(2), pages 433-452, February.
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Cited by:
- Chien-Chih Wang & Yi-Ying Yang, 2023. "A Machine Learning Approach for Improving Wafer Acceptance Testing Based on an Analysis of Station and Equipment Combinations," Mathematics, MDPI, vol. 11(7), pages 1-14, March.
- Peng Zhan & Shaokun Wang & Jun Wang & Leigang Qu & Kun Wang & Yupeng Hu & Xueqing Li, 2021. "Temporal anomaly detection on IIoT-enabled manufacturing," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1669-1678, August.
- Tobias Schlosser & Michael Friedrich & Frederik Beuth & Danny Kowerko, 2022. "Improving automated visual fault inspection for semiconductor manufacturing using a hybrid multistage system of deep neural networks," Journal of Intelligent Manufacturing, Springer, vol. 33(4), pages 1099-1123, April.
- Hasan Tercan & Philipp Deibert & Tobias Meisen, 2022. "Continual learning of neural networks for quality prediction in production using memory aware synapses and weight transfer," Journal of Intelligent Manufacturing, Springer, vol. 33(1), pages 283-292, January.
- Jinwoo Song & Prashant Kumar & Yonghawn Kim & Heung Soo Kim, 2024. "A Fault Detection System for Wiring Harness Manufacturing Using Artificial Intelligence," Mathematics, MDPI, vol. 12(4), pages 1-17, February.
- Hasan Tercan & Tobias Meisen, 2022. "Machine learning and deep learning based predictive quality in manufacturing: a systematic review," Journal of Intelligent Manufacturing, Springer, vol. 33(7), pages 1879-1905, October.
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Keywords
Fault detection and diagnosis; Time series classification; Deep learning; Convolutional neural network; Smart manufacturing;All these keywords.
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