Please use this identifier to cite or link to this item: http://dspace.ensta.edu.dz/jspui/handle/123456789/326
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dc.contributor.authorBOUCHIREB, Bouthaina-
dc.contributor.authorBELAHMRABET, Dhiyaa eddine-
dc.contributor.authorSALHI, Nedjma (Directeur de thèse)-
dc.date.accessioned2025-03-12T08:39:53Z-
dc.date.available2025-03-12T08:39:53Z-
dc.date.issued2024-
dc.identifier.urihttp://dspace.ensta.edu.dz/jspui/handle/123456789/326-
dc.descriptionMaster: Programme Complémentaire d'Ingéniorat: Management et ingénierie de la maintenance industrielle : Alger: Ecole Nationale Supérieure des Technologie Avancées(ex ENST): 2024en_US
dc.description.abstractThe advent of Industry 4.0 has ushered in a new era of smart manufacturing. Artificial Intelligence (AI), and more specifically, machine learning, standsat the forefront of this transformation, offering unprecedented opportunities forpredictive maintenance. This article delves into the crucial role of AI, particularly machine learning algorithms, in the context of Industry 4.0, emphasizingtheir significance in predictive maintenance applications. The article explores howmachine learning models used in predictive maintenance can be divided according to their role. Predictive maintenance not only reduces downtime, but alsoimproves overall operational efficiency. The integration of artificial intelligenceand machine learning technologies promotes the shift from reactive to proactivemaintenance strategies, thus improving resource use and extending the life of industrial assets. However, despite promising progress, the application of machinelearning in predictive maintenance is not without challenges. The article discusseskey obstacles such as data quality and accessibility, problems in choosing machinelearning models, and the need to adapt to dynamic industrial environments. Itdiscusses the importance of creating a robust data infrastructure and developingtransparent models to build trust in AI-based predictive maintenance systems.en_US
dc.language.isoenen_US
dc.publisherENSTAen_US
dc.subjectSmart Maintenanceen_US
dc.subjectArtificial Intelligence (AI)en_US
dc.subjectMachine Learning (ML)en_US
dc.subjectPredictive Maintenanceen_US
dc.subjectfault predictionen_US
dc.subjectCondition Monitoringen_US
dc.subjectIndustry 4.0en_US
dc.subjectInternet of Things (IoT)en_US
dc.subjectCyber-Physical System (CPS)en_US
dc.titleAI in Predictive Maintenance for Industry 4.0 - an overview.en_US
dc.typeArticleen_US
Appears in Collections:ART- Génie Industriel ( Management et Ingénierie de la Maintenance Industrielle)

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