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A production-repairing inventory model considering demand and the proportion of defective items as rough intervals

Author

Listed:
  • Subhendu Ruidas

    (Sonamukhi College)

  • Mijanur Rahaman Seikh

    (Sonamukhi College
    Kazi Nazrul University)

  • Prasun Kumar Nayak

    (Midnapore College(Autonomous))

Abstract

This paper explores a production inventory model in an imperfect production system under a rough interval environment. The occurrences of shortages are allowed and are fully backlogged. In this paper, two models are presented. In the first model, the demand of the product is considered as a rough interval. In the second model, both the demand and the defective rate are considered as rough intervals. In reality, these two factors cannot be assessed exactly due to a lack of available data. Moreover, there are few scenarios where the demand of the product is assessed in two-layer information. The inner layer demand is obvious, and it may extend up to the outer layer depending on the situation. Also, the same thing may happen for the defective rate of the product. In those cases, it is more reasonable to express the demand and the defective rate as rough intervals instead of fuzzy or interval numbers. Based on the expected value of rough intervals, the necessary and sufficient conditions are determined analytically to obtain the optimal inventory policies. The main advantage of this method is that the optimal profit and the optimal lot size are determined as crisp numbers rather than rough intervals. Obtaining a precise value for these two quantities is desirable for any production manager. Numerical examples for both models are provided to illustrate the solution methodology. Sensitivity analysis of the optimal solutions concerning the key parameters is conducted for identifying several managerial implications.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:operea:v:22:y:2022:i:3:d:10.1007_s12351-021-00634-5
    DOI: 10.1007/s12351-021-00634-5
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    References listed on IDEAS

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    1. Sudarshan Bardhan & Haimanti Pal & Bibhas Chandra Giri, 2019. "Optimal replenishment policy and preservation technology investment for a non-instantaneous deteriorating item with stock-dependent demand," Operational Research, Springer, vol. 19(2), pages 347-368, June.
    2. Naoufel Cheikhrouhou & Biswajit Sarkar & Baishakhi Ganguly & Asif Iqbal Malik & Rafael Batista & Young Hae Lee, 2018. "Optimization of sample size and order size in an inventory model with quality inspection and return of defective items," Annals of Operations Research, Springer, vol. 271(2), pages 445-467, December.
    3. Tapan Kumar Datta, 2017. "Inventory system with defective products and investment opportunity for reducing defective proportion," Operational Research, Springer, vol. 17(1), pages 297-312, April.
    4. Gour Chandra Mahata, 2013. "Application of fuzzy sets theory in an EOQ model for items with imperfect quality and shortage backordering," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 14(4), pages 466-490.
    5. 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.
    6. Asif Iqbal Malik & Biswajit Sarkar, 2019. "Coordinating Supply-Chain Management under Stochastic Fuzzy Environment and Lead-Time Reduction," Mathematics, MDPI, vol. 7(5), pages 1-28, May.
    7. Subhendu Ruidas & Mijanur Rahaman Seikh & Prasun Kumar Nayak, 2020. "An EPQ model with stock and selling price dependent demand and variable production rate in interval environment," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 385-399, April.
    8. Madhukar Nagare & Pankaj Dutta & Pravin Suryawanshi, 2020. "Optimal procurement and discount pricing for single-period non-instantaneous deteriorating products with promotional efforts," Operational Research, Springer, vol. 20(1), pages 89-117, March.
    9. B. C. Giri & S. Sharma, 2016. "Optimal ordering policy for an inventory system with linearly increasing demand and allowable shortages under two levels trade credit financing," Operational Research, Springer, vol. 16(1), pages 25-50, April.
    10. Nita H. Shah & Dushyantkumar G. Patel & Digeshkumar B. Shah, 2018. "EPQ model for returned/reworked inventories during imperfect production process under price-sensitive stock-dependent demand," Operational Research, Springer, vol. 18(2), pages 343-359, July.
    11. D.K. Jana & K. Maity & T.K. Roy, 2013. "Multi-objective imperfect production inventory model in fuzzy rough environment via genetic algorithm," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 18(4), pages 365-385.
    12. Jaber, M.Y. & Goyal, S.K. & Imran, M., 2008. "Economic production quantity model for items with imperfect quality subject to learning effects," International Journal of Production Economics, Elsevier, vol. 115(1), pages 143-150, September.
    13. R. Patro & Mitali M. Nayak & M. Acharya, 2019. "An EOQ model for fuzzy defective rate with allowable proportionate discount," OPSEARCH, Springer;Operational Research Society of India, vol. 56(1), pages 191-215, March.
    14. Salameh, M. K. & Jaber, M. Y., 2000. "Economic production quantity model for items with imperfect quality," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 59-64, March.
    15. Evan L. Porteus, 1986. "Optimal Lot Sizing, Process Quality Improvement and Setup Cost Reduction," Operations Research, INFORMS, vol. 34(1), pages 137-144, February.
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