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Application of Renewable Energy in Production and Supply Chain Management II

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 8069

Special Issue Editor

Special Issue Information

Dear Colleagues,

Nowadays, environmental issues are very prominent, which involve seeking to reduce the effect of global warming. The increasing rate of carbon emission due to industrialization is one of the causes of global warming. Renewable energy resources are naturally replenishing fuel sources, most notably solar, wind, biomass, geothermal, and hydro power. Unlike nuclear power and fossil fuels (coal, oil, and natural gas), renewables provide clean, safe, and reliable power, with low-carbon emissions. Thus, applying renewable energy in production and supply chain management is very much essential to protect the environment. The idea of applying renewable energy in supply chain management is to enhance environmental sustainability. As environmental sustainability is very crucial nowadays for the industrial sector, the aim of this Special Issue is to combine a revolution of the industrial sector with sustainable supply chain management under the influence of renewal energy. The objective of this Special Issue is the improvement of the inventory, production, supply chain management, and logistics regarding sustainability under the surveillance of supply channels.

Prof. Dr. Biswajit Sarkar
Guest Editor

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Keywords

  • Green manufacturing under renewable energy
  • Supply chain management
  • Effect of energy in supply chain management
  • Consumption of energy during production
  • Sustainability
  • Energy effect in transportation
  • Biomass energy
  • Biofuel energy
  • Renewable energy sources
  • Effect of energy in inventory management
  • Renewable energy supply chain management
  • Effect of energy in green supply chain management

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Published Papers (2 papers)

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Research

19 pages, 1372 KiB  
Article
Impact of Energy and Carbon Emission of a Supply Chain Management with Two-Level Trade-Credit Policy
by Vandana, S. R. Singh, Dharmendra Yadav, Biswajit Sarkar and Mitali Sarkar
Energies 2021, 14(6), 1569; https://doi.org/10.3390/en14061569 - 12 Mar 2021
Cited by 60 | Viewed by 4001
Abstract
Supply chain management aims to integrate environmental thinking with efficient energy consumption into supply chain management. It includes a flexible manufacturing process, more product delivery to customers, optimum energy consumption, and reduced waste. The manufacturing process can be made more flexible through volume [...] Read more.
Supply chain management aims to integrate environmental thinking with efficient energy consumption into supply chain management. It includes a flexible manufacturing process, more product delivery to customers, optimum energy consumption, and reduced waste. The manufacturing process can be made more flexible through volume agility. In this scenario, production cannot be constant, and with the concept of volume agility, production is taken as a decision variable under the effect of optimum energy consumption. Considering a two-echelon supply chain, we consider a producer and supplier with two-level-trade-credit policies (TLTCP) with the optimum consumption. To reduce the integrated total inventory cost, we believe that demand is a function of the credit period and selling price. The cost function is analyzed, either with the credit period dependent demand rate or with the selling price dependent demand rate through the numerical examples under energy costs. Energy and carbon emission costs are introduced in setup/ordering cost, holding cost, and item cost for producer and supplier. The effect of inflation on the total cost cannot be ignored; this model is being developed for deteriorating items with the simultaneous impact of volume agility, energy, carbon emission cost, and two-level-trade-credit policies with inflation. This supply chain model was solved analytically and obtained the optimum decision variables in a quasi-closed form solution. An illustrative theorem is being utilized to analyze the optimum result for all the decision parameters. The convexity of the objective function is being obtained analytically as well as graphically. Finally, numerical examples and sensitivity analysis are employed to illustrate the present study and with managerial insights. Full article
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14 pages, 566 KiB  
Article
Effect of Renewable Energy to Reduce Carbon Emissions under a Flexible Production System: A Step Toward Sustainability
by Mitali Sarkar and Byung Do Chung
Energies 2021, 14(1), 215; https://doi.org/10.3390/en14010215 - 3 Jan 2021
Cited by 19 | Viewed by 3040
Abstract
Renewable energy and environmental issues are receiving considerable attention worldwide along with the technological development of production system for reducing global warming. Due to the use of smart technologies, the rate of carbon emission and energy utilization have become very high and are [...] Read more.
Renewable energy and environmental issues are receiving considerable attention worldwide along with the technological development of production system for reducing global warming. Due to the use of smart technologies, the rate of carbon emission and energy utilization have become very high and are directly related to different industries. This study focuses on the effect of renewable energy on the advancement of smart production with a flexible production rate as well as the reduction of carbon emission to build a sustainable smart production system. A mathematical model is developed to maximize the profit of the smart production system for economic development while considering technological and environmental issues. The model is solved analytically, and we obtain closed and quasi-closed form solutions. A numerical experiment is performed, and a comparison with previous studies indicates that our method achieves more profit than existing ones. Additionally, we highlight the major effect of renewable energy. Different graphical representations of the decision variables prove the convergence of the model. A sensitivity analysis and graphical representation are presented in this paper, and some recommendations for industry are provided by simulating this model in different scenarios. Full article
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