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My bibliography Save this articleJoint modeling of classification and regression for improving faulty wafer detection in semiconductor manufacturing
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DOI: 10.1007/s10845-018-1447-2
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References listed on IDEAS
- Chen-Fu Chien & Chiao-Wen Liu & Shih-Chung Chuang, 2017. "Analysing semiconductor manufacturing big data for root cause detection of excursion for yield enhancement," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5095-5107, September.
- Chien-Chang Hsu & Min-Sheng Chen, 2016. "Intelligent maintenance prediction system for LED wafer testing machine," Journal of Intelligent Manufacturing, Springer, vol. 27(2), pages 335-342, April.
- Manjeevan Seera & Chee Peng Lim & Chu Kiong Loo, 2016. "Motor fault detection and diagnosis using a hybrid FMM-CART model with online learning," Journal of Intelligent Manufacturing, Springer, vol. 27(6), pages 1273-1285, December.
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Cited by:
- Jiyoung Song & Young Chul Lee & Jeongsu Lee, 2023. "Deep generative model with time series-image encoding for manufacturing fault detection in die casting process," Journal of Intelligent Manufacturing, Springer, vol. 34(7), pages 3001-3014, October.
- Sangho Lee & Youngdoo Son, 2021. "Motor Load Balancing with Roll Force Prediction for a Cold-Rolling Setup with Neural Networks," Mathematics, MDPI, vol. 9(12), pages 1-21, June.
- Wenhan Fu & Chen-Fu Chien & Lizhen Tang, 2022. "Bayesian network for integrated circuit testing probe card fault diagnosis and troubleshooting to empower Industry 3.5 smart production and an empirical study," Journal of Intelligent Manufacturing, Springer, vol. 33(3), pages 785-798, March.
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Keywords
Faulty wafer detection; Predictive modeling; Joint modeling; Neural network; Semiconductor manufacturing;All these keywords.
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