Documents dont l'auteur est "Shaban, Yasser"

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Ali, A. M., Yacout, S., Rabeih, E.-A., & Shaban, Y. (2022). A cyber process control system based on pattern recognition and cloud computing. Gestão & Produção, 29. Lien externe

Ali, A. M., Mohamed, E.-A., Yacout, S., & Shaban, Y. (2020). Cloud computing based unsupervised fault diagnosis system in the context of Industry 4.0. Gestão & Produção, 27(3), 19 pages. Disponible

Aly, M., Yacout, S., & Shaban, Y. (janvier 2017). Analysis of massive industrial data using MapReduce framework for parallel processing [Communication écrite]. 63rd Annual Reliability and Maintainability Symposium (RAMS 2017), Orlando, FL (6 pages). Lien externe

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Bassetto, S., Yacout, S., Bassetto, S., & Shaban, Y. (2023). Experimental vibration data collected for a belt drive system under different operating conditions. Data in Brief, 48, 6 pages. Disponible

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Elsheikh, A., Yacout, S., Ouali, M.-S., & Shaban, Y. (2020). Failure time prediction using adaptive logical analysis of survival curves and multiple machining signals. Journal of Intelligent Manufacturing, 31(2), 403-415. Lien externe

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Gonzalez Rubio, J. L., Shaban, Y., & Yacout, S. (mars 2016). Visual data mining of faults in machining process based on machine learning [Communication écrite]. International Conference on Industrial Engineering and Operations Management (IEOM 2016), Kuala Lumpur, Malaysia. Lien externe

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Khalifa, R. M., Yacout, S., Bassetto, S., & Shaban, Y. (2024). Condition monitoring and warning of a belt drive system based on a logical analysis of data regression-based residual control chart. Structural Health Monitoring. Lien externe

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Shaban, Y., Yacout, S., & Aly, M. (janvier 2017). Condition-based reliability prediction based on logical analysis of survival data [Communication écrite]. 63rd Annual Reliability and Maintainability Symposium (RAMS 2017), Orlando, FL (6 pages). Lien externe

Shaban, Y., Yacout, S., Balazinski, M., & Jemielniak, K. (2017). Cutting tool wear detection using multiclass logical analysis of data. Machining Science and Technology, 21(4), 526-541. Lien externe

Shaban, Y., & Yacout, S. (mars 2016). Identifying optimal intervene hazard for cutting tools considering cost-availability optimization [Communication écrite]. International Conference on Industrial Engineering and Operations Management (IEOM 2016), Kuala Lumpur, Malaysia. Lien externe

Shaban, Y., & Yacout, S. (2016). Predicting the remaining useful life of a cutting tool during turning titanium metal matrix composites. Proceedings of the Institution of Mechanical Engineers. Part B, Journal of Engineering Manufacture, 232(4), 681-689. Lien externe

Shaban, Y., Aramesh, M., Yacout, S., Balazinski, M., Attia, H., & Kishawy, H. (2015). Optimal replacement times for machining tool during turning titanium metal matrix composites under variable machining conditions. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 231(6), 924-932. Lien externe

Shaban, Y. (2014). Diagnosis of Machining Conditions Based on Logical Analysis of Data [Thèse de doctorat, École Polytechnique de Montréal]. Disponible

Shaban, Y., Aramesh, M., Yacout, S., Balazinski, M., Attia, H., & Kishawy, H. (mai 2014). Optimal replacement of tool during turning titanium metal matrix composites [Communication écrite]. IIE Annual Conference and Expo 2014, Montréal, Québec. Non disponible

Shaban, Y., Meshreki, M., Yacout, S., Balazinski, M., & Attia, H. (2014). Process control based on pattern recognition for routing carbon fiber reinforced polymer. Journal of Intelligent Manufacturing, 28(1), 165-179. Lien externe

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Taha, H. A., Yacout, S., & Shaban, Y. (2023). Online failure analysis and autonomous risk control scheme for electric buses. Engineering Failure Analysis, 154, 15 pages. Lien externe

Taha, H. A., Yacout, S., & Shaban, Y. (2022). Autonomous self-healing mechanism for a CNC milling machine based on pattern recognition. Journal of Intelligent Manufacturing, 34(5), 2185-2205. Lien externe

Taha, H. A., Yacout, S., & Shaban, Y. (2022). Deep reinforcement learning for autonomous pre-failure tool life improvement. International Journal of Advanced Manufacturing Technology, 121(9-10), 6169-6192. Lien externe