IDEAS home Printed from https://ideas.repec.org/a/ids/ijpman/v17y2023i4p507-540.html
   My bibliography  Save this article

Multi-item sustainable manufacturing model for cleaner production system under imprecise demand and random defective rate

Author

Listed:
  • Saif Sami
  • S.K. Shon
  • Dharmendra Yadav

Abstract

The present study revisits the multi-item economic production quantity model by considering that the production process is not perfect due to planned backorder. The present study aims to make the production system as a cleaner production system by considering a reworking process for random defective items which is uniformly distributed. In addition to this, to make the production system cleaner, an investment is made to control the production process. Based on the reworking time, two different inventory models are proposed under the effect of uncertainty in demand. Impreciseness in demand is handled by applying fuzzy set theory. Centroid method is applied to defuzzify the objective function. The global optimal solution is derived by using a nonlinear optimisation technique. Numerical analysis with sensitive analysis is provided to illustrate the proposed model. From analysis it is observed that due to increase in investment, 98% reduction in waste management cost and 11% reduction in total cost is observed. Thus, investment in system improvement is helpful to achieve the task of clean production. The study also highlighted the advantage of outsourcing for a cleaner environment. In the end, sensitivity analyses are also carried out, and managerial insights are provided.

Suggested Citation

  • Saif Sami & S.K. Shon & Dharmendra Yadav, 2023. "Multi-item sustainable manufacturing model for cleaner production system under imprecise demand and random defective rate," International Journal of Procurement Management, Inderscience Enterprises Ltd, vol. 17(4), pages 507-540.
  • Handle: RePEc:ids:ijpman:v:17:y:2023:i:4:p:507-540
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=132145
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

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

    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:ids:ijpman:v:17:y:2023:i:4:p:507-540. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=255 .

    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.