| Titre : |
Developing a planning panel to forecast truck fleet size based on activity forecast |
| Type de document : |
document électronique |
| Auteurs : |
Oussama Rahmani, Auteur ; Salah Eddine Adjabi, Auteur ; Iskander Zouaghi, Directeur de thèse |
| Editeur : |
[S.l.] : [s.n.] |
| Année de publication : |
2025 |
| Importance : |
1 fichier PDF (4.4 Mo) |
| Présentation : |
ill. |
| Note générale : |
Mode d'accès : accès au texte intégral par intranet.
Mémoire de Projet de Fin d’Études : Génie Industriel.Management industriel : Alger, École Nationale Polytechnique : 2025
Bibliogr. p. 90 - 93 .- Annexe p. 94 - 107 |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Oil and Gas Services
Supply Chain Optimization
Mathematical Modeling
Decision Support Tools
Supply chain planning
Planning adherence
Dynamic Scheduling |
| Index. décimale : |
PI02525 |
| Résumé : |
This thesis addresses inefficiencies in SLB Algeria’s domestic logistics by developing an integrated solution composed of a planning tool, an optimization model, and a performance dashboard. The planning panel, built in Excel VBA, improves visibility over job schedules, truck allocation, and material requirements. A mixed-integer linear programming model is implemented to retrospectively determine the minimum truck fleet needed to fulfill past demand while respecting operational constraints. A Power BI dashboard visualizes key performance indicators to assess efficiency and support decision-making.
Findings show that data-driven tools significantly improve planning accuracy, fleet utilization, and visibility. However, challenges remain regarding data integration, shipment consolidation logic, and tool scalability, indicating directions for future research. |
Developing a planning panel to forecast truck fleet size based on activity forecast [document électronique] / Oussama Rahmani, Auteur ; Salah Eddine Adjabi, Auteur ; Iskander Zouaghi, Directeur de thèse . - [S.l.] : [s.n.], 2025 . - 1 fichier PDF (4.4 Mo) : ill. Mode d'accès : accès au texte intégral par intranet.
Mémoire de Projet de Fin d’Études : Génie Industriel.Management industriel : Alger, École Nationale Polytechnique : 2025
Bibliogr. p. 90 - 93 .- Annexe p. 94 - 107 Langues : Anglais ( eng)
| Mots-clés : |
Oil and Gas Services
Supply Chain Optimization
Mathematical Modeling
Decision Support Tools
Supply chain planning
Planning adherence
Dynamic Scheduling |
| Index. décimale : |
PI02525 |
| Résumé : |
This thesis addresses inefficiencies in SLB Algeria’s domestic logistics by developing an integrated solution composed of a planning tool, an optimization model, and a performance dashboard. The planning panel, built in Excel VBA, improves visibility over job schedules, truck allocation, and material requirements. A mixed-integer linear programming model is implemented to retrospectively determine the minimum truck fleet needed to fulfill past demand while respecting operational constraints. A Power BI dashboard visualizes key performance indicators to assess efficiency and support decision-making.
Findings show that data-driven tools significantly improve planning accuracy, fleet utilization, and visibility. However, challenges remain regarding data integration, shipment consolidation logic, and tool scalability, indicating directions for future research. |
|
PI00100 
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