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DC Field | Value | Language |
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dc.contributor.author | BRAHIM, MAZARI Ridha | - |
dc.contributor.author | GHOMARI, Leila (Directeur de thèse) | - |
dc.date.accessioned | 2025-03-12T08:29:33Z | - |
dc.date.available | 2025-03-12T08:29:33Z | - |
dc.date.issued | 2024 | - |
dc.identifier.uri | http://dspace.ensta.edu.dz/jspui/handle/123456789/323 | - |
dc.description | Master: Programme Complémentaire d'Ingéniorat: Management et ingénierie de la maintenance industrielle: Alger: Ecole Nationale Supérieure des Technologie Avancées(ex ENST): 2024 | en_US |
dc.description.abstract | In 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.iso | en | en_US |
dc.publisher | ENSTA | en_US |
dc.subject | Process Mining | en_US |
dc.subject | Maintenance | en_US |
dc.subject | Optimization | en_US |
dc.subject | Event Logs | en_US |
dc.subject | Data-driven Maintenance | en_US |
dc.title | Process mining for maintenance purposes | en_US |
dc.type | Article | en_US |
Appears in Collections: | ART- Génie Industriel ( Management et Ingénierie de la Maintenance Industrielle) |
Files in This Item:
File | Description | Size | Format | |
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Article MFE BRAHIM MAZARI - GHOMARI Leila.pdf | Master: Programme Complémentaire d'Ingéniorat | 982.47 kB | Adobe PDF | View/Open |
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