IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v15y2024i3d10.1007_s13198-023-02202-w.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-023-02202-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-023-02202-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alamri, Adel A. & Syntetos, Aris A., 2018. "Beyond LIFO and FIFO: Exploring an Allocation-In-Fraction-Out (AIFO) policy in a two-warehouse inventory model," International Journal of Production Economics, Elsevier, vol. 206(C), pages 33-45.
    2. Chen, Liang-Hsuan & Kang, Fu-Sen, 2010. "Coordination between vendor and buyer considering trade credit and items of imperfect quality," International Journal of Production Economics, Elsevier, vol. 123(1), pages 52-61, January.
    3. Oshmita Dey, 2019. "A fuzzy random integrated inventory model with imperfect production under optimal vendor investment," Operational Research, Springer, vol. 19(1), pages 101-115, March.
    4. Dey, O. & Giri, B.C., 2014. "Optimal vendor investment for reducing defect rate in a vendor–buyer integrated system with imperfect production process," International Journal of Production Economics, Elsevier, vol. 155(C), pages 222-228.
    5. Bhunia, A.K. & Shaikh, Ali Akbar, 2015. "An application of PSO in a two-warehouse inventory model for deteriorating item under permissible delay in payment with different inventory policies," Applied Mathematics and Computation, Elsevier, vol. 256(C), pages 831-850.
    6. Manoranjan De & Barun Das & Manoranjan Maiti, 2016. "EPL models for complementary and substitute items under imperfect production process with promotional cost and selling price dependent demands," OPSEARCH, Springer;Operational Research Society of India, vol. 53(2), pages 259-277, June.
    7. Liao, Jui-Jung & Chung, Kun-Jen & Huang, Kuo-Nan, 2013. "A deterministic inventory model for deteriorating items with two warehouses and trade credit in a supply chain system," International Journal of Production Economics, Elsevier, vol. 146(2), pages 557-565.
    8. Bikash Koli Dey & Hyesung Seok, 2024. "Intelligent inventory management with autonomation and service strategy," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 307-330, January.
    9. Mahesh Kumar Jayaswal & Mandeep Mittal, 2022. "Impact of Inflation and Credit Financing Policy on the Supply Chain With Learning," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 15(1), pages 1-25, January.
    10. Vandana & Shiv Raj Singh & Mitali Sarkar & Biswajit Sarkar, 2023. "Effect of Learning and Forgetting on Inventory Model under Carbon Emission and Agile Manufacturing," Mathematics, MDPI, vol. 11(2), pages 1-20, January.
    11. Wang, Chih-Hsiung, 2005. "Integrated production and product inspection policy for a deteriorating production system," International Journal of Production Economics, Elsevier, vol. 95(1), pages 123-134, January.
    12. Katherinne Salas-Navarro & Whady F. Florez & Leopoldo Eduardo Cárdenas-Barrón, 2024. "A vendor-managed inventory model for a three-layer supply chain considering exponential demand, imperfect system, and remanufacturing," Annals of Operations Research, Springer, vol. 332(1), pages 329-371, January.
    13. Mahesh Kumar Jayaswal & Mandeep Mittal & Isha Sangal, 2021. "Ordering policies for deteriorating imperfect quality items with trade-credit financing under learning effect," 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. 12(1), pages 112-125, February.
    14. Bimal Kumar Sett & Bikash Koli Dey & Biswajit Sarkar, 2020. "Autonomated Inspection Policy for Smart Factory—An Improved Approach," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
    15. Basim S. O. Alsaedi, 2024. "A Sustainable Supply Chain Model with a Setup Cost Reduction Policy for Imperfect Items under Learning in a Cloudy Fuzzy Environment," Mathematics, MDPI, vol. 12(10), pages 1-33, May.
    16. 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.
    17. Tseng-Fung Ho & Chi-Chung Lin & Chih-Ling Lin, 2020. "Determining the Optimal Inventory and Number of Shipments for a Two-Resource Supply Chain with Correlated Demands and Remanufacturing Products Allowing Backorder," Mathematics, MDPI, vol. 8(4), pages 1-16, April.
    18. Ashoke Kumar Bera & Dipak Kumar Jana, 2017. "Multi-item imperfect production inventory model in Bi-fuzzy environments," OPSEARCH, Springer;Operational Research Society of India, vol. 54(2), pages 260-282, June.
    19. M. Palanivel & R. Uthayakumar, 2016. "Two-warehouse inventory model for non-instantaneous deteriorating items with partial backlogging and inflation over a finite time horizon," OPSEARCH, Springer;Operational Research Society of India, vol. 53(2), pages 278-302, June.
    20. Ivan Darma Wangsa & Hui Ming Wee & Shih-Hsien Tseng, 2019. "A coordinated vendor–buyer system considering loss and damage claims, insurance cost and stochastic lead time," 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. 10(3), pages 384-398, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:ijsaem:v:15:y:2024:i:3:d:10.1007_s13198-023-02202-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.