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International audience; 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.

International audience; LPG Loading /unloading site is considered as a dangerous environment of significant risk, especially during LPG transfer operations. These risks may cause catastrophic dangers such as BLEVE (Boiling Liquid Expanding Vapour Explosion), UVCE (Unconfined Vapour Cloud Explosion), etc. The site consists of a tank (RST) containing LPG and threetransfer posts. Two posts allow loading of small carrier tankers 6 tons. The other one transfer post transfer LPG contained injumbo tankers 20 tons inside the tank. The industrial site at risks chooses to demonstrate the need for a modelling-simulation approach. The aim is to check first compliance and authorization of the truck when it enters the site for loading /unloading, to verify the authorization to make the transfer, and then, to identify the driver and his training to ensure that the transfer operations are going to take place without incident. Sometimes, it may happen that Consignment Operator (CO) is busy orabsent and thus the driver operates alone without being authorized, in this case the site risks a loss of control due to a lack of resources. The modelling-simulation will be done using multi-agent systems that will present the drivers, trucks, PO and loading unloading posts as agents in order to have a model facilitating this checking.