Reducing carbon emissions of a multi-stage smart production for biofuel towards sustainable development

被引:45
作者
Kugele, Andreas Se Ho [1 ]
Sarkar, Biswajit [1 ,2 ]
机构
[1] Yonsei Univ, Dept Ind Engn, 50 Yonsei Ro, Seoul 03722, South Korea
[2] Saveetha Univ, Saveetha Inst Med & Tech Sci, Saveetha Dent Coll, Ctr Transdisciplinary Res CFTR, 162 Poonamallee High Rd, Chennai 600077, Tamil Nadu, India
关键词
Smart production; Biofuel; Autonomation; Sustainability; Renewable energy; SUPPLY CHAIN MANAGEMENT; COST; ALGORITHM; DELIVERY; PICKUP;
D O I
10.1016/j.aej.2023.01.003
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Governmental mandates and financial benefits are the leading factors that encourage any industrialist to adopt sustainable practices and environmental measures. Carbon emissions and waste occur at several stages during the manufacturing process of biofuel, and it requires a thorough inspection and an accurate strategy for each stage. Using smart technologies in multi-stage production, a sustainable model is developed for the biofuel manufacturing industry to reduce carbon emissions and waste from an economical perspective. Impurities due to unreliability are removed from the biofuel at each stage of the production process. A mathematical model is provided to obtain the optimum production policy for biofuel using renewable energy. During transportation, fuel consumption is one of the most significant sources of carbon emissions, which makes optimizing fuel consumption necessary to minimize these emissions. The fuel consumption of biofuel-related freight transportation is minimized under an integrated scheduling policy. The suggestions in this study enable the manufacturer to reduce the total cost by 11.13%, while increasing sustainability and controlling carbon emissions. The biggest impact originates from the considered transportation policy. Implementing an optimized transportation policy is less complicated and financially more accessible for the management with substantial environmental and greater economical benefits compared to smart production. (c) 2023 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/ licenses/by-nc-nd/4.0/).
引用
收藏
页码:93 / 113
页数:21
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