Quality monitoring in multistage manufacturing systems by using machine learning techniques
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Industrial and Manufacturing Engineering,Software
Link
https://link.springer.com/content/pdf/10.1007/s10845-021-01792-1.pdf
Reference77 articles.
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3. Amini, M., & Chang, S. I. (2018). MLCPM: A process monitoring framework for 3D metal printing in industrial scale. Computers and Industrial Engineering, 124, 322–330. https://doi.org/10.1016/j.cie.2018.07.041
4. Amini, M., & Chang, S. I. (2020). Intelligent data-driven monitoring of high dimensional multistage manufacturing processes. International Journal of Mechatronics and Manufacturing Systems, 13(4), 299–322. https://doi.org/10.1504/IJMMS.2020.112352
5. Arif, F., Suryana, N., & Hussin, B. (2013a). Cascade quality prediction method using multiple PCA+ID3 for multi-stage manufacturing system. IERI Procedia, 4, 201–207. https://doi.org/10.1016/j.ieri.2013.11.029
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