Abstract

Biofuel manufacturing from renewable biomass through a smart manufacturing system is an important alternative to fossil fuels, which helps to decrease dependability on conventional fuel and decrease carbon emanations. By utilizing efficient labors, smart machines, and minimized energy utilization, the conventional biofuel manufacturing framework can be converted into a smart sustainable manufacturing framework. The existing conventional fuel demand can be replaced by biofuel. This study efforts to make pure biofuel with less amount of carbon emanations and energy utilization through a smart multi-type biofuel manufacturing framework, where the demand of the biofuel is selling price dependent. The different energy costs including air handling cost, lighting cost are calculated in this work-in-process inventory. The carbon emissions cost is included in every stage of this model. A variable demand has introduced for the maximization of profit. To reduce energy consumption and carbon emissions, a two-stage inspection cost with a variable manufacturing rate is taken to make the manufacturing process flexible such that the amount of impure biofuel is minimized. Although a random manufacturing rate is applied through a smart manufacturing system, still impure biofuel is manufactured. The impure biofuel is remanufactured again through refining just after the well-planned manufacturing ends. In this model, the multi-delivery technique is used such that a fixed amount of biofuel of n segments of the pure biofuel is transported to market places at predetermined intervals at the time of delivery frame. The classical optimization technique is used for continuous and differentiable variables and the mixed integer programming technique is utilized for discrete variables to maximize the total profit globally. To validate the model’s usefulness, four numerical observations are studied. It is shown that by utilizing the said procedure, the percentage of impure biofuel can be decreased truly through the minimized energy consumption. The graphical representation and the sensitivity experiment show the impact of every parameter with the whole cost of the research paper. Numerical results assist to get the maximum profit and the optimum selling price of biofuel globally in a sustainable smart multi-type biofuel manufacturing system.

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