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Reduction of Pollution through Sustainable and Flexible Production by Controlling By-Products

D. Yadav1, R. Singh2, A. Kumar2, and B. Sarkar3,4 *

  1. Department of Mathematics, Vardhaman College, MJP Rohilkhand University, Uttar Pradesh 246701, India
  2. Meerut College, Western Kutchery Rd, Meerut, Uttar Pradesh 250003, India
  3. Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Sinchon-dong, Seodaemun-gu, Seoul 03722, South Korea
  4. Center for Transdisciplinary Research (CFTR), Saveetha Dental College, Saveetha Institute of Medical and Technical Sciences, Saveetha University, 162 Poonamallee High Road, Velappanchavadi, Chennai, Tamil Nadu 600077, India

*Corresponding author. Tel.: +82-10-7498-1981. E-mail address: (B. Sarkar).


Every manufacturing system produces toxic by-products that cause a hazardous impact on society and the environment. As a result, pollution control authorities’ role has gained importance for the betterment of society and the preservation of a clean and green environment. As a result, one of the goals of this research is to develop a sustainable smart manufacturing model with less waste and controlled pollution. Here, a flexible production process is discussed under imprecise market conditions with partial backlogging and rework. Two different sustainable production models are presented here by considering pollution control costs. A sustainable production model with variable pollution costs is examined under the influence of three pollution control mechanisms to improve the model’s applicability. A solution methodology, including three critical theorems, is provided to obtain the optimal production rate, length, and total cost per cycle. The paper’s novelty lies in introducing pollution control costs and pollution control mechanisms together in a flexible, sustainable production system with uncertainty. In comparison to the other models, the model with a variable pollution cost appears to be more sustainable as, in this case, there is a 25.5% reduction in the pollution level compared to the other models. Implementing three pollution-controlling strategies, such as pollution cap, pollution cap and trade, and pollution tax, resulted in reductions of 34.37, 0.83, and 0.62% in pollution levels, respectively. A sensitivity analysis of the obtained results is carried out to show the model’s strength and robustness.

Keywords: pollution control, imperfect quality, flexible production, rework, partial backlogging, fuzziness

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