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An imperfect production model with shortage and screening constraint under time varying demand

Author

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  • Madhusudan Dolai

    (Vidyasagar University)

  • Shyamal Kumar Mondal

    (Vidyasagar University)

Abstract

This study presents an imperfect production inventory model in which shortages occur depending on the screening rate of the produced items in the manufacturing system. Since in the system, there may exist some unplanned events, such as machinery faults and labor issues etc., so the screening rate cannot be predicted by the manufacturer. Henceforth, here it has been considered as a variable because of disruptions in the screening process which creates complexity in the manufacturer’s demand fulfillment process. Now, on the basis of screening rate, there may exist two cases. In the first case, the screening rate of perfect items is higher than the demand rate, that means, there is no shortage during the demand fulfillment process. On the other hand, the screening rate of perfect items is lower than the demand rate. In this case, shortages may occurred in the system. In this investigation, a time dependent non-linear demand function has also been considered. Additionally, the screening cost of the product depends on the screening rate. The objective of this study is to find the optimum values of the production rate, screening rate, and business period in such a way that the manufacturer’s profit is maximized. Compairing two cases, we find that imperfectness and shortages have a negative impact on the average profit. The screening fraction parameter has positive impact on the average profit of the manufacturer. Also, sensitivity analysis is provided and some managerial insights are concluded for two cases.

Suggested Citation

  • Madhusudan Dolai & Shyamal Kumar Mondal, 2024. "An imperfect production model with shortage and screening constraint under time varying demand," 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. 15(3), pages 1183-1202, March.
    • Handle: RePEc:spr:ijsaem:v:15:y:2024:i:3:d:10.1007_s13198-023-02202-w
    DOI: 10.1007/s13198-023-02202-w
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    References listed on IDEAS

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    1. 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.
    2. Hsiao, Yu-Cheng, 2008. "Integrated logistic and inventory model for a two-stage supply chain controlled by the reorder and shipping points with sharing information," International Journal of Production Economics, Elsevier, vol. 115(1), pages 229-235, September.
    3. Pankaj Narang & Pijus Kanti De, 2023. "An imperfect production-inventory model for reworked items with advertisement, time and price dependent demand for non-instantaneous deteriorating item using genetic algorithm," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 24(1), pages 53-77.
    4. Ravi Shankar Kumar & A. Goswami, 2015. "EPQ model with learning consideration, imperfect production and partial backlogging in fuzzy random environment," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(8), pages 1486-1497, June.
    5. Lee, Chun Chen & Hsu, Shu-Lu, 2009. "A two-warehouse production model for deteriorating inventory items with time-dependent demands," European Journal of Operational Research, Elsevier, vol. 194(3), pages 700-710, May.
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    Cited by:

    1. Goutam Mandal & Amalesh Kumar Manna & Subhash Chandra Das & Asoke Kumar Bhunia, 2025. "Optimization of a deteriorated inventory model with bi-level credit periods and variable demand via tournament teaching learning based optimization algorithm," 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. 16(5), pages 1689-1710, May.

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