By using renewable biomass, the advancement in biofuel production through a smart inspection production framework is a crucial substitute to fossil fuels which support minimizing environmental pollution and zero carbon emissions. Traditional biofuel production can be converted into a sustainable smart production system by utilizing smart machines, skilled labor, and reduced energy consumption. The prime purpose of this study is to produce pure biofuel with less energy consumption and carbon emissions through a smart production framework of biofuel. The work-in-process inventory is calculated for different costs, including air handling, lighting, and carbon emissions, in each stage of the study. Although smart variable production is utilized, still impure biofuel is produced with a random production rate. The impure biofuel is purified to make it pure. A multi-delivery technique is used such that a fixed amount of biofuel of n segments of the pure biofuel is transported to the market as per the market's demand. The total profit of this study is maximized globally with the help of the classical optimization technique. Four numerical examples are observed to validate the model. The applicability and efficiency of the proposed model are finally demonstrated through a real case study in India. Two special cases prove the necessity of smart production and discrete investment for setup cost reduction. The sensitivity analysis and the graphical representation give each parameter's effect on the model's total profit. Numerical results prove that if no discrete investment for setup cost reduction and fixed production rate is taken, the common production cycle time is increased remarkably. It is seen that the total profit of this study rises 4.30% from the traditional production system. Moreover, numerical results prove a major effect on renewable energy in a sustainable smart production system.
|Publication status||Published - 2023 Mar 15|
Bibliographical noteFunding Information:
The work is supported by the National Research Foundation of Korea (NRF) grant, funded by the Korea Government (MSIT) ( NRF-2020R1F1A1064460 ).
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All Science Journal Classification (ASJC) codes
- Chemical Engineering(all)
- Fuel Technology
- Energy Engineering and Power Technology
- Organic Chemistry