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    http://dspace.ensta.edu.dz/jspui/handle/123456789/383Full metadata record
| DC Field | Value | Language | 
|---|---|---|
| dc.contributor.author | ZERROUK, Ikram Feth Ezahr | - | 
| dc.contributor.author | GUENDOUZI, Meriem Lydia | - | 
| dc.contributor.author | REZGUI, Wail (Directeur de thèse) | - | 
| dc.date.accessioned | 2025-11-03T11:55:44Z | - | 
| dc.date.available | 2025-11-03T11:55:44Z | - | 
| dc.date.issued | 2025 | - | 
| dc.identifier.uri | http://dspace.ensta.edu.dz/jspui/handle/123456789/383 | - | 
| dc.description | Master : Programme Complémentaire d'Ingéniorat: Management et ingénierie de la maintenance industrielle : Alger: Ecole Nationale Supérieure des Technologie Avancées: 2025 | en_US | 
| dc.description.abstract | The emergence of Industry 4.0 has significantly reshaped industrial maintenance by promoting the integration of intelligent technologies that enhance efficiency, reliability, and data-driven decision-making. Traditional Computerized Maintenance Management Systems (CMMS), once focused solely on planning and documentation, are now evolving into smart platforms capable of supporting real-time monitoring, predictive analytics, and automated maintenance workflows. This paper explores the integration of Industry 4.0 technologies such as IoT, Artificial Intelligence, and Augmented Reality within CMMS environments. It highlights commonly adopted solutions, identifies key limitations and discusses futures opportunities such as integrating emerging technologies like digital twins and advanced AI tools, including Natural Language Processing (NLP) and Large Language Models (LLM). This work aims to provide insights into building next-generation CMMS aligned with the principles of Industry 4.0. | en_US | 
| dc.language.iso | en | en_US | 
| dc.publisher | ENSTA | en_US | 
| dc.subject | Industry 4.0 | en_US | 
| dc.subject | Next generation CMMS | en_US | 
| dc.subject | Maintenance Process Optimization | en_US | 
| dc.subject | AI-Powered Decision | en_US | 
| dc.subject | Making | en_US | 
| dc.subject | Smart Maintenance | en_US | 
| dc.title | Integration of CMMS in Industry 4.0 | en_US | 
| dc.title.alternative | Towards an AI-Driven Maintenance Management System | en_US | 
| dc.type | Thesis | en_US | 
| Appears in Collections: | ART- Génie Industriel ( Management et Ingénierie de la Maintenance Industrielle) | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ART-MIMI 06-25 ZERROUK Ikram & GUENDOUZI Meriem _ MIMI 2025 _ REZGUI Wail & AMRANI Mohamed - REZGUI Wail.pdf | Master : Programme Complémentaire d'Ingéniorat | 1.68 MB | Adobe PDF | View/Open | 
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