Please use this identifier to cite or link to this item: http://dspace.ensta.edu.dz/jspui/handle/123456789/323
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dc.contributor.authorBRAHIM, MAZARI Ridha-
dc.contributor.authorGHOMARI, Leila (Directeur de thèse)-
dc.date.accessioned2025-03-12T08:29:33Z-
dc.date.available2025-03-12T08:29:33Z-
dc.date.issued2024-
dc.identifier.urihttp://dspace.ensta.edu.dz/jspui/handle/123456789/323-
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.abstractIn production-related sectors, maintenance is a critical element of operational efficiency. This paper examines the evolution of process mining. This technique utilizes event data to analyze and optimize real-world business processes, specifically focusing on its application in the context of maintenance objectives. Introducing a systematic approach, the methodology enriches maintenance event logs with contextual depth and goes through phases such as data preprocessing, process exploration definition, and performance analysis. The article highlights the central role of process mining in maintenance but also delves into its implementation's significant challenges and limitations. The article also provides key considerations for organizations considering process mining in their maintenance strategies.en_US
dc.language.isoenen_US
dc.publisherENSTAen_US
dc.subjectProcess Miningen_US
dc.subjectMaintenanceen_US
dc.subjectOptimizationen_US
dc.subjectEvent Logsen_US
dc.subjectData-driven Maintenanceen_US
dc.titleProcess mining for maintenance purposesen_US
dc.typeArticleen_US
Appears in Collections:ART- Génie Industriel ( Management et Ingénierie de la Maintenance Industrielle)

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