Improving Productivity through Linear Programming: A Case of Oil Refinery Industry 2020-01-5128

In recent years, the petroleum industry has faced an unpredictable and increasingly unstable market. This instability causes drastic fluctuations in the oil prices, which in turn affects the demand for the product. Refineries have confronted an impossible situation, where if crude oil is purchased at a certain price, in a matter of days for a what-so-ever reason the oil prices take a hit and they are forced to sell the oil at a lower price, which is not desirable. If the refinery gambles to buy bulk of crude oil at a bargain, the literature suggests that the chances are of a decrease in a product demand due to increasing oil price, which again is not desirable. Moreover, refinery industries also have to face the consequences of rapidly changing exchange rates. In situations like this, it becomes essential for the refineries to reduce losses as much as possible, increase productivity, and reduce the cost of its operations. In this research, techniques of linear programming (LP) were used to increase the productivity of processing plant’s high-speed diesel, kerosene, naphtha, vacuum gas oil, and vacuum residue. For this, a model was developed to achieve the optimized productivities of all the products in a single blend. Productions were simulated on the results obtained by the developed model. It was found that the developed model can effectively reduce the associated cost and deliver the current production quantity much quicker. Further, the proposed scheme produced promising and better results than the currently available methods (commercial software).