Justifiable Logistic Network Management: A Production Model for Optimizing Energy Use, Cost, and Carbon Radiations

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ID: 310416
2023
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Ranked #63 of 409 articles by views in International Journal of Science and Social Science Research

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Abstract
Automating the manufacturing process is a top priority for many businesses today because it allows them to increase output while maintaining quality, which is essential for quickly responding to client demands. This pattern has resulted in a progressive shift in technology, with the inevitable consequence of a rise in energy demand. In order to prevent the need for increased energy consumption for improved manufacturing technology in industrialized countries, academics have begun working on continual development in conjunction with cleaner-energy regulations. In addition to nuclear weapons, global warming caused by human-produced greenhouse gases is another major problem in our society today. So as to make up for the energy need and lower the carbon balance for cleaner manufacturing, renewable energies like insolation have expanded rapidly in recent years. This paper discusses the Logistic Network management of the automotive industry with its suppliers in order to maximize production while simultaneously minimizing costs, reducing carbon exhalation and making the most of renewable energy sources. This analysis considers a scenario where providers monitor and control faulty products as an outsourced service. The suggested mathematical model considers sustainable suppliers and is solved using a loaded goal programming approach. The model's responsiveness to changes in energy use is evaluated across a range of scenarios. Documentation of successful down-to-earth use in the automotive industry includes minimum production costs and carbon emissions. Considering the manufacturer and suppliers, the results verify the model's potential to provide a foundation for sustainability in the logistics network environment.
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imported_1768931386_696fc03a04655 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Pralay Poria
Journal International Journal of Science and Social Science Research
Year 2023
DOI
10.5281/zenodo.13509910
URL
https://www.ijsssr.com/j/article/view/112
Keywords Keywords not found

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