Abstract
Today's industry presents many challenges whose the competitiveness weighs heavily on productivity. The future industry or industry 4.0 requires a new way for organizing industrial processes and must integrate smarter maintenance tools capable of greater adaptability in production. This new organization must respond to competitiveness challenges to achieve customer expectations but with a short deadline to market and an optimized cost production in terms of energy consumed reduced breakdowns, etc. One of the failures encountered in the industry, object of our study, is the unbalance corresponds to a rotor imbalance, shaft … due to the non-coincidence of the principal axe of inertia and the inertia center with the rotation axis. Our contribution is to develop the main components surveillance of an industrial installation continuously and follow the evolution through quantifiable and qualifiable data which allows preventing a dysfunction before stopping the production. This surveillance uses very precise predictive maintenance technologies and can tracks parameters in real time: vibration, consumed energy and the various components temperature.
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Mukesh PS, Bulsara A (2016) Energy loss due to unbalance in rotor–shaft system. J Eng Des Technol 14(2):277–362
Saleem MA, Diwakar G, Satyanarayana MRS (2012) Detection of unbalance in rotating machines using shaft deflection measurement during its operation. J Mech Civ Eng (IOSR-JMCE) 3(3):8–20
Elkhatib A (2007) Energy consumption and machinery vibrations. In: International conference on sound and vibrations, ICSV14, Cairns 9–12 July, pp 1–6
Ahmat Fadil A (2019) Proposition d’une architecture de surveillance Holonique pour l’aide à la maintenance proactive d’une flotte de systèmes mobiles: application au domaine ferroviaire. Thèse de doctorat, Valenciennes
Jeffali F, Ouariach A, El Kihel A, Nougaoui A (2019) Infrared thermography-based diagnosis of the impact on the kinematic chain. Mater Today Proc 13:949–955
Abouelanouar B, Elamrani M, Elkihel B, Delaunois F (2018) Application of wavelet analysis and its interpretation in rotating machines monitoring and fault diagnosis. Int J Eng Technol (UAE) 7:3465–3471
Bakdid et al (2017) Welding control using ultrasonic multi-elements method. JMES 8:3483–3489
Jeffali F, Ouariach A, El Kihel B, Nougaoui A (2019) Diagnosis of three-phase induction motor and the impact on the kinematic chain using non-destructive technique of infrared thermography. J Infrared Phys Technol 102:102970
Bakdid A, El Kihel B, Nougaoui A, Delaunois F (2019) Three-dimensional characterization of weld defects in a steel material. J Eng Appl Sci 14:1928–1932
Bouzidi Z (2018) Pronostic des systèmes industriels basé sur l’intelligence artificielle Maintenance prédictive. thèse de doctorat, Faculté des Sciences Exactes et des Sciences de la Nature et de la Vie Département d’informatique,Université Mohamed Khider—BISKRA
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Elkihel, A., Elkihel, Y., Bakdid, A., Gziri, H., Derouiche, I. (2022). Contribution to the Optimization of Industrial Energy Efficiency by Intelligent Predictive Maintenance Tools Case of an Industrial System Unbalance. In: Bennani, S., Lakhrissi, Y., Khaissidi, G., Mansouri, A., Khamlichi, Y. (eds) WITS 2020. Lecture Notes in Electrical Engineering, vol 745. Springer, Singapore. https://doi.org/10.1007/978-981-33-6893-4_12
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DOI: https://doi.org/10.1007/978-981-33-6893-4_12
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