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A Constrained Production System Involving Production Flexibility and Carbon Emissions

Author

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  • Asif Iqbal Malik

    (Department of Industrial and Management Engineering, Incheon National University, 119, Academy-ro, Yeonsu-gu, Incheon 22012, Korea)

  • Byung Soo Kim

    (Department of Industrial and Management Engineering, Incheon National University, 119, Academy-ro, Yeonsu-gu, Incheon 22012, Korea)

Abstract

The proposed study presents an economic lot size and production rate model for a single vendor and a single buyer setup. This model involves greenhouse gas (GHG) emissions from industrial sources. The carbon emissions in this model are considered as two types: direct emissions and indirect emissions. The production rate affects carbon emissions generation in production, i.e., generally, higher production rates result in more emissions, which is governable in many real-life cases. The production rate also impacts the process reliability and quality. Faster production deteriorates the production system quickly, leading to machine failure and defective items. Such reliability and quality problems increase energy consumptions and supply chain (SC) costs. This paper formulates a vendor-buyer SC model that tackles these issues. It considers two decision-making policies: integrated or centralized as well as decentralized, where the aim is to obtain the optimal values of the decision variables that give the minimum total SC cost. It includes the costs of setup, holding inventory, carbon emissions, order processing, production, reworking, and inspection processes. The decision variables are the production rate, lead time, order quantity, the number of shipments, and the investments for setup cost reduction. In the later sections, this paper compares the numerical outcomes of the two centralized and decentralized policies. It also provides sensitivity analysis and useful insights on the economic and environmental execution of the SC.

Suggested Citation

  • Asif Iqbal Malik & Byung Soo Kim, 2020. "A Constrained Production System Involving Production Flexibility and Carbon Emissions," Mathematics, MDPI, vol. 8(2), pages 1-21, February.
  • Handle: RePEc:gam:jmathe:v:8:y:2020:i:2:p:275-:d:322488
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    References listed on IDEAS

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    3. Subhendu Ruidas & Mijanur Rahaman Seikh & Prasun Kumar Nayak, 2022. "A production-repairing inventory model considering demand and the proportion of defective items as rough intervals," Operational Research, Springer, vol. 22(3), pages 2803-2829, July.
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    5. Behnamfar, Reza & Sajadi, Seyed Mojtaba & Tootoonchy, Mahshid, 2022. "Developing environmental hedging point policy with variable demand: A machine learning approach," International Journal of Production Economics, Elsevier, vol. 254(C).

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