E3S Web Conf.
Volume 351, 202210th International Conference on Innovation, Modern Applied Science & Environmental Studies (ICIES’2022)
|Number of page(s)||5|
|Published online||24 May 2022|
- A. Al-Fuqaha, M. Guisani, M. Mohammadi, M. Aledhari, and M. Ayyash, Internet of Things: A Survey on Enabling Technologies, Protocols, and Applications. IEEE Commun. Surv. Tutor, 17, 4, pp. 2347–2376 (2015). [CrossRef] [Google Scholar]
- C. Okoh, R. Roy, and J. Mehnen, Predictive Maintenance Modelling for Through-Life Engineering Services, Procedia CIRP, 59,196–201 (2017). [Google Scholar]
- L. Silvestri, A. Forcina, V. Introna, A. Santolamazza, and V. Cesarotti, Maintenance transformation through Industry 4.0 technologies: A systematic literature review, Comput. Ind., 123, 103335 (2020). [CrossRef] [Google Scholar]
- B. Einabadi, A. Baboli, and M. Ebrahimi, Dynamic Predictive Maintenance in industry 4.0 based on real time information: Case study in automotive industries. IFAC-Pap., 52, 13, 1069–1074 (2019). [Google Scholar]
- T. Zonta, C. A. da Costa, R. da Rosa de Lima Righi, M. J., E.S. da Trindade, and G. P. Li, Predictive maintenance in the industry 4.0: A systematic literature review, Comput. Ind. Eng., 150, 106889 (2020). [CrossRef] [Google Scholar]
- A. El Kihel, Y. El Kihel, A. Bakdid, H. Gziri, I. Manssouri, D. Amegouz, Optimization of industrial energy efficiency by intelligent predictive maintenance tools case of misalignment of an industrial system, in IEEE 2nd International Conference on Electronics, Control, Optimization and Computer Science, ICECOCS, 9314505 (2020). [Google Scholar]
- A. Elkihel, I. Derouiche, Y. Elkihel, A. Bakdid, and H. Gziri, Artificial intelligence based on the neurons networks at the service predictive bearing”, in 6th International Conference on Wireless Technologies, Embedded and Intelligent Systems (WITS-2020), Morocco, Fez (2020). (to be published) [Google Scholar]
- R. K. Mobley, An introduction to predictive maintenance 2nd ed, Amsterdam, New York: Butterworth-Heinemann (2002). [Google Scholar]
- A. Abu-Samah, M. K. Shahzad, E. Zamai, and A. B. Said, Failure Prediction Methodology for Improved Proactive Maintenance using Bayesian Approach, IFAC-Pap., 48, 844–851, (2015). [Google Scholar]
- S. Selcuk, Predictive maintenance, its implementation and latest trends, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 9, 1670–1679, (2016). [Google Scholar]
- T. P. Carvalho, F. A. A. M. N. Soares, R. Vita, R.P. da Francisco, J. P. Basto, and S. G. S. Alcala, A systematic literature review of machine learning methods applied to predictive maintenance, Comput. Ind. Eng., 137, 106024 (2019) [CrossRef] [Google Scholar]
- J. Wan et al., A Manufacturing Big Data Solution for Active Preventive Maintenance, IEEE Trans. Ind. Inform., 13, vol. 4, pp. 2039–2047, 2017. [CrossRef] [Google Scholar]
- L. Atzori, A. Iera, and G. Morabito, The Internet of Things: A survey, Comput. Netw., 54, 2787–2805 (2010) [Google Scholar]
- D. G. S. Pivoto, L. F. F. de Almeida, R. da Rosa Righi, J. J. P. C. Rodrigues, A. B. Lugli, and A. M. Alberti, Cyber-physical systems architectures for industrial internet of things applications in Industry 4.0: A literature review, J. Manuf. Syst., 58,176–192 (2021). [CrossRef] [Google Scholar]
- T. P. Carvalho, F. A. A. M. N. Soares, R. Vita, R. da P. Francisco, J. P. Basto, and S. G. S. Alcala, A systematic literature review of machine learning methods applied to predictive maintenance, Comput. Ind. Eng., 137, 106024 (2019). [CrossRef] [Google Scholar]
- J. Wan et al., A Manufacturing Big Data Solution for Active Preventive Maintenance, IEEE Trans. Ind. Inform., 13, 2039–2047, (2017). [CrossRef] [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.