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

Authors: Saif Sami; S.K. Shon; Dharmendra Yadav

Addresses: College of Business Administration, Al-Yamamah University, Riyadh, Kingdom of Saudi Arabia ' Department of Mathematics, Vardhaman College, Bijnor (UP), India; Affiliated to: MJPR University, Bareilly, India ' Department of Mathematics, Vardhaman College, Bijnor (UP), India; Affiliated to: MJPR University, Bareilly, India

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.

Keywords: cleaner production; rework; random defective rate; multi-item; screening process.

DOI: 10.1504/IJPM.2023.132145

International Journal of Procurement Management, 2023 Vol.17 No.4, pp.507 - 540

Received: 28 Oct 2021
Accepted: 12 Jan 2022
Published online: 12 Jul 2023 *

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