Equipment electrocardiogram (EECG): making intelligent production line more robust
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Industrial and Manufacturing Engineering,Software
Link
https://link.springer.com/content/pdf/10.1007/s10845-023-02177-2.pdf
Reference58 articles.
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3. Bampoula, X., Siaterlis, G., Nikolakis, N., & Alexopoulos, K. (2021). A deep learning model for predictive maintenance in cyber-physical production systems using LSTM autoencoders. Sensors, 21(3), 972. https://doi.org/10.3390/s21030972
4. Bonci, A., Longhi, S., Nabissi, G., & Verdini, F. (2019). Predictive maintenance system using motor current signal analysis for industrial robot. In 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). https://doi.org/10.1109/ETFA.2019.8869067
5. Bortolini, M., Galizia, F. G., & Mora, C. (2018). Reconfigurable manufacturing systems: Literature review and research trend. Journal of Manufacturing Systems, 49, 93–106. https://doi.org/10.1016/j.jmsy.2018.09.005
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