Risk analysis of maintenance activities in a LPG supply chain with a Multi-Agent approach

Maryam Gallab 1, 2, * Hafida Bouloiz 3 Emmanuel Garbolino 1 Mohamed Tkiouat 2 Mohamed Ali Elkilani 1 Nicolas Bureau 4
* Auteur correspondant
1 CRC - Centre de recherche sur les Risques et les Crises
2 LERMA - Laboratoire d'Etudes et Recherche en Mathématiques Appliquées
3 LG2I - Laboratoire du génie industriel et informatique
4 PRIMAGAZ Company
Abstract : This paper aims to present a new systemic modelling approach using the unified modelling language (UML) and Multi-Agents Systems (MAS) to model the complexity and analyze the risks of maintenance activities within a Liquefied Petroleum Gas (LPG) supply chain. This approach is a two steps corresponding to Modelling & Simulation and Risk Analysis. Based on a multi-agent simulator, the objective is to consider the complexity of maintenance tasks of supply chain equipment to better understand risks and to identify abnormal and accident prone situations. The case study is LPG supply chain located in France. AnyLogic simulator is used to assess safety of this supply chain. Through simulation, this proposed approach provides a whole view to ease understanding of maintenance activities within LPG supply chain and to lead to effective analysis of its safety. The final goal is orienting maintenance actors to the best risk minimizing decisions.
Keywords : AnyLogic platform Multi-agent approach Modelling & simulation LPG supply chain Maintenance Risk analysis
Type de document :
Article dans une revue
Liste complète des métadonnées
https://hal-mines-paristech.archives-ouvertes.fr/hal-01497282
Contributeur : Magalie Prudon <>
Soumis le : mardi 28 mars 2017 - 14:54:07
Dernière modification le : lundi 12 novembre 2018 - 10:59:44

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ENSMP | INSTITUT-TELECOM | CRC-PARISTECH | CRC-THESE | ENSMP_CRC | PSL | PARISTECH

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Maryam Gallab, Hafida Bouloiz, Emmanuel Garbolino, Mohamed Tkiouat, Mohamed Ali Elkilani, et al.. Risk analysis of maintenance activities in a LPG supply chain with a Multi-Agent approach. Journal of Loss Prevention in the Process Industries, Elsevier, 2017, 47, pp.41 - 56. ⟨10.1016/j.jlp.2017.02.026⟩. ⟨hal-01497282⟩

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