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How does an industry manage the optimum cash flow within a smart production system with the carbon footprint and carbon emission under logistics framework?

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  • Sarkar, Biswajit
  • Guchhait, Rekha
  • Sarkar, Mitali
  • Cárdenas-Barrón, Leopoldo Eduardo

Abstract

The optimized cash flow may affect any smart production system to control a material requirement planning and to reduce the carbon footprint within the environment. An automation policy is utilized within a smart production system under a forward and a backward logistics system. Such logistic network generally consists of a well-structured transportation system, which may increase the carbon footprint. This study deals how the carbon footprint can be controlled by a smart production system and it obtains the net present value of products for the four sub-systems associated with the logistics system. To investigate this, four sub-systems as manufacturing, distribution, consumption, and remanufacturing are implemented. A solution methodology is designed with an integral transformation through the frequency domain. This smart logistics system can be used by an associated matrix through an input-output analysis based on the distribution center. An illustrative numerical experiment is conducted and the study reveals that the discounted sale in disposal subsection at the end of the logistic cycle gives high positive impact, where the efficiency is increased due to discarding defective products by the automation policy. Graphical studies on the effect of transportation time for the total net present value and the net present value for disposal items are compared. It is found that two-stage inspection process reveals less amount of defective items and less pollution. As the closed-loop supply chain management is considered and due to transportation, huge amount of carbon emissions are passing through the environment, this study gives the reduced amount of carbon and more perfect products by an optimum cash-flow within a smart production system under advanced logistics management.

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  • Sarkar, Biswajit & Guchhait, Rekha & Sarkar, Mitali & Cárdenas-Barrón, Leopoldo Eduardo, 2019. "How does an industry manage the optimum cash flow within a smart production system with the carbon footprint and carbon emission under logistics framework?," International Journal of Production Economics, Elsevier, vol. 213(C), pages 243-257.
    • Handle: RePEc:eee:proeco:v:213:y:2019:i:c:p:243-257
    DOI: 10.1016/j.ijpe.2019.03.012
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    References listed on IDEAS

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    Cited by:

    1. Panagiotis Trivellas & Georgios Malindretos & Panagiotis Reklitis, 2020. "Implications of Green Logistics Management on Sustainable Business and Supply Chain Performance: Evidence from a Survey in the Greek Agri-Food Sector," Sustainability, MDPI, vol. 12(24), pages 1-29, December.
    2. Jihed Jemai & Biswajit Sarkar, 2019. "Optimum Design of a Transportation Scheme for Healthcare Supply Chain Management: The Effect of Energy Consumption," Energies, MDPI, vol. 12(14), pages 1-27, July.
    3. Rekha Guchhait & Sarla Pareek & Biswajit Sarkar, 2019. "How Does a Radio Frequency Identification Optimize the Profit in an Unreliable Supply Chain Management?," Mathematics, MDPI, vol. 7(6), pages 1-19, May.
    4. Mitali Sarkar & Byung Do Chung, 2021. "Effect of Renewable Energy to Reduce Carbon Emissions under a Flexible Production System: A Step Toward Sustainability," Energies, MDPI, vol. 14(1), pages 1-14, January.
    5. Weihua Liu & Shangsong Long & Yanjie Liang & Jinkun Wang & Shuang Wei, 2023. "The influence of leadership and smart level on the strategy choice of the smart logistics platform: a perspective of collaborative innovation participation," Annals of Operations Research, Springer, vol. 324(1), pages 893-935, May.
    6. Dominguez, Roberto & Cannella, Salvatore & Framinan, Jose M., 2021. "Remanufacturing configuration in complex supply chains," Omega, Elsevier, vol. 101(C).
    7. Mitali Sarkar & Biswajit Sarkar, 2019. "Optimization of Safety Stock under Controllable Production Rate and Energy Consumption in an Automated Smart Production Management," Energies, MDPI, vol. 12(11), pages 1-16, May.
    8. Iqra Asghar & Biswajit Sarkar & Sung-jun Kim, 2019. "Economic Analysis of an Integrated Production–Inventory System under Stochastic Production Capacity and Energy Consumption," Energies, MDPI, vol. 12(16), pages 1-27, August.
    9. T. V. S. R. K. Prasad & Kolla Srinivas & C. Srinivas, 2020. "Investigations into control strategies of supply chain planning models: a case study," OPSEARCH, Springer;Operational Research Society of India, vol. 57(3), pages 874-907, September.
    10. Ullah, Mehran & Sarkar, Biswajit, 2020. "Recovery-channel selection in a hybrid manufacturing-remanufacturing production model with RFID and product quality," International Journal of Production Economics, Elsevier, vol. 219(C), pages 360-374.
    11. Darya Pyatkina & Tamara Shcherbina & Vadim Samusenkov & Irina Razinkina & Mariusz Sroka, 2021. "Modeling and Management of Power Supply Enterprises’ Cash Flows," Energies, MDPI, vol. 14(4), pages 1-17, February.
    12. Shahzad, Umer & Ferraz, Diogo & Nguyen, Huu-Huan & Cui, Lianbiao, 2022. "Investigating the spill overs and connectedness between financial globalization, high-tech industries and environmental footprints: Fresh evidence in context of China," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    13. Guitao Zhang & Xiao Zhang & Hao Sun & Xinyu Zhao, 2021. "Three-Echelon Closed-Loop Supply Chain Network Equilibrium under Cap-and-Trade Regulation," Sustainability, MDPI, vol. 13(11), pages 1-26, June.
    14. Suchitra Pattnaik & Mitali Madhusmita Nayak & Stefano Abbate & Piera Centobelli, 2021. "Recent Trends in Sustainable Inventory Models: A Literature Review," Sustainability, MDPI, vol. 13(21), pages 1-20, October.
    15. Shin, Youngchul & Lee, Sangyoon & Moon, Ilkyeong, 2021. "Robust multiperiod inventory model with a new type of buy one get one promotion: “My Own Refrigerator”," Omega, Elsevier, vol. 99(C).
    16. Mariusz Kmiecik, 2022. "Logistics Coordination Based on Inventory Management and Transportation Planning by Third-Party Logistics (3PL)," Sustainability, MDPI, vol. 14(13), pages 1-19, July.
    17. Wu, Chengfeng & Liu, Xin & Li, Annan, 2021. "A loss-averse retailer–supplier supply chain model under trade credit in a supplier-Stackelberg game," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 182(C), pages 353-365.
    18. Shib Sankar Sana, 2022. "A structural mathematical model on two echelon supply chain system," Annals of Operations Research, Springer, vol. 315(2), pages 1997-2025, August.
    19. Xia, Jing & Niu, Wenju, 2021. "Carbon-reducing contract design for a supply chain with environmental responsibility under asymmetric information," Omega, Elsevier, vol. 102(C).

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