A Simulation Based Approach for Evaluating the Impact of Maritime Transport on the Inventory Levels of an Oil Supply Chain

One of the most important objectives of a manufacturing company is the optimization of the distribution of the produced goods considering the whole value chain. Unfortunately, in many companies the performance of the supply chain depends on many uncertain factors that are difficult to predict. The only way to face them is to adopt innovative solutions and tools that allow a swift response to the market changes. This paper analyzes the distribution processes managed by the logistics department of a large company producing and distributing petroleum products through the following main steps: crude oil’s transportation typically from many countries to a refinery; refining process; maritime transportation from the refinery to three costal depots; road transport from depots to gas stations. The analyzed process is the primary supply, consisting in the maritime transport from the refinery to the coastal depots, liable to stochastic activities and events as weather condition. Through simulating the primary supply, we study the effects that the ship traffic generates on the overall variance of inventory levels at the costal depots with respect to specific inventory level targets, and analyze the impact of different tactical decision choices on the variance reduction. Reducing inventory’s variance, through a better control of the distribution, allows the company to reduce inventory target levels and hence to reduce inventory costs in term of capital stock, while keeping the same risk level of stock out. The project is made of many phases: map all relevant processes to have a complete vision of transport’s structure; conduct a statistical analysis to identify specific statistical distributions of every ships’ process (delay, mooring, loading, etc.); model and simulate the primary supply using simulation software; use the model to make a “what-if” analysis. Within this project, it has been possible to realize a model that presents stochastic elements. All these phases are supported by six-sigma methodology, which focalizes on defects' process reduction by the control of its mean square deviation and following the stages of the DMAIC (Define Measure Analyze Improve Control). One of the what-if analysis which has been done consists in simulating the opening refinery’s jetties h24, because currently these are closed during the night. Opening the jetties, will increase the capacity of some of the bottleneck resources for the oil distribution process, and thanks to the simulation model we can estimate quickly the effects on the oil transport system.