American J. of Engineering and Applied Sciences 3 (1): 138-143, 2010 ISSN 1941-7020 © 2010 Science Publications Corresponding Author: Razman Mat Tahar, Faculty of technology Management, University Malaysia Pahang, Kuantan, Malaysia 138 A Novel Transporting System Model for Oil Refinery Razman Mat Tahar and Waleed K. Abduljabbar Faculty of technology Management, University Malaysia Pahang, Kuantan, Malaysia Abstract: Problem statement: Oil refineries are widely used to store various liquids and gases. Petroleum products are in high demand. Oil companies have abundant resources of petroleum products in pipelines and storage tanks. Approach: Included are storage tanks at retail gasoline station, home heating oil tanks, lubricant storage at automotive service facilities, propane tanks in all sorts of application, and oil company terminals across the world. The aim of this study is to present a model by which a decision maker should be able to choose the optimal number of tanks, tank size and truck arrival rate to maximize average total profit per week for an oil terminal operation. Results: In this study, oil terminal modeled by using a discrete event simulation program Arena for AL-Dura refinery, Baghdad, Iraq. Multifactor variance analysis is used to determine different levels of the three factors and their interactions significantly affect the terminal profit including the optimal number of tanks, size of tanks and trucks of the arrival rate to maximize total revenue on average per week. Conclusion/Recommendations: The result showed minimum cost of oil at the terminal and tanker truck fill rates and price and income structure, also predict with 90% confidence levels, a number of factors, which gives highest average total income per week Key words: Refinery operations, petroleum, transportation, supply chain policies INTRODUCTION Oil terminals are widely used to store various liquids and gases such as chemicals, crude oil and natural gas. Petroleum products are in high demand for heating, manufacturing, vehicle fuel, lubricants and more. Comprehensive overview of the work associated with the optimization in oil refinery chain interestingly, a similar trend is observed for refinery modeling the supply chain. Most work on refineries food chain modeling reported in the literature only one address of the chain, such as crude logistics using discrete event simulation and optimal control (Neiro and Pinto, 2004; Reddy et al., 2004). As recent research efforts advance in several converging areas of science and technology, how the orientation of management science in mobile is that of joint problem solving (Hughes, 1971). He sets up a network model to determine where to locate the terminals with respect to customer distribution sites. The efficient ways of loading and unloading into and out of storage tanks at oil terminals (Christofides et al., 1980). The transportation costs involved in loading and unloading these storage tanks are not investigated, additionally the article does not address the terminal profits. Simulation-based short-term scheduling of crude oil from port to refinery tanks and distillation unit, agent-based crude procurement (Cheng and Duran, 2004; Chryssolouris et al., 2005; Julka et al., 2002). External the refinery environment (Banks et al., 2002), Supply Chain Management (SCM) simulation studies at IBM and Virtual Logistics and talk about issues related to strategic and operational SCM, distributed SCM simulation and commercial packages for SCM simulation (Kleijnen, 2005). Make a distinction four types of simulation-spreadsheet simulation, system dynamics, discrete-event simulation and business games and give a literature review of the application of each type in SCM (Jung et al., 2004). Propose a simulation-based optimization computational framework for determining safety stock levels for planning and scheduling applications. They combine deterministic planning and scheduling models for optimization and a discrete-event simulation model. Their job is focused on planning and scheduling (Suresh et al., 2008). Developed Integrated Refinery In Silico (IRIS), an integrated model of all the entities in the refinery supply chain, so as to enable integrated and matched decision making. In this study, Oil refineries model have abundant resources of petroleum products in pipelines and storage tanks. Included are storage tanks at retail gasoline station, home heating oil tanks, lubricant storage at automotive service facilities, propane tanks in