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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. [Display omitted] [ABSTRACT FROM AUTHOR]

Increasing energy demand and the rising levels of greenhouse gas emissions have increased the necessity of bioenergy and sustainable energy generation. The sustainable bioenergy supply chain is the key to produce sustainable biofuel. This paper points to render an optimization model for planning a versatile and dependable biomass-to-bioenergy sustainable supply chain network in which crop residuals from several agricultural sectors, multi-transportation disruption modes, multi-biorefineries, multi-biogas plants, and multi-market centers are investigated for two bioenergy sources, namely biofuel and biogas. For this reason, supply chain cost optimization, emissions of feedstock transport, processing, and distributing end biofuel to respective markets are utilized. The multi-setup-multi-delivery (MSMD) concept is incorporated and lead time crashing cost is applied to minimize the lead time in this model. The carbon emission costs at all steps and the variable production rate for the production of bioenergy are included within the model. Finally, one small-scale data and another large-scale data of six agricultural areas, four biorefineries, four biogas plants, and six markets are considered to validate the model's usefulness. The model's goal is to show bioenergy's effect to make a sustainable supply chain of biofuel and biogas. The numerical results reveal that the cost of bioenergy production contributed 54.12%, a major extent of the whole cost in biorefinery and biogas plants. The transportation segment is the preeminent initiator of carbon emissions with 83.33% in the entire carbon emission within the whole supply chain. Although, transportation cost contributed 33.09% of the total cost, the multi setup-delivery-multi-delivery policy minimized the whole supply chain cost. The results provide a systematic guideline for developing a sustainable biofuel supply-chain by minimizing cost, various aspects of transportation logistics, and multi-model alternatives under reduced energy effects. • Energy demand and two approaches of biofuel and biogas production are evaluated. • Reduction of the supply chain network's total cost. • Optimizing allocation of the appropriate quantity of residual biomass and biofuel. • Reducing energy consumption by using variable production rate. • An intelligent logistics system with multi-disruption is addressed. [ABSTRACT FROM AUTHOR]