A JOINT INVENTORY MODEL WITH RELIABILITY, CARBON EMISSION, AND INSPECTION ERRORS IN A DEFECTIVE PRODUCTION SYSTEM

  • Isha SANGAL Department of Mathematics & Statistics, Banasthali Vidyapith, Rajasthan, 304 022, India
  • Bijoy Kumar SHAW Department of Mathematics & Statistics, Banasthali Vidyapith, Rajasthan, 304 022, India
  • Biswajit SARKAR Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Sinchon-dong, Seodaemun-gu, Seoul-038722, South Korea
  • Rekha GUCHHAIT Department of Mathematics & Statistics, Banasthali Vidyapith, Rajasthan, 304 022, India

Abstract

Nowadays, the environment is an important concern of industries parallel to the economy. In this direction, a joint vendor-buyer model is exhibited where the system
reliability and inspection errors are discussed along with the carbon emission issue. The main goal of this model is to obtain the optimum investment, shipment size, reliability, and lead time even the inspection errors present in the system. A reliability dependent unit production cost is utilized to raise the machinery system reliability. Transportation of products uses the single-setup-multi-unequal-delivery (SSMUD) policy reduced carbon emission. The mathematical problem is solved analytically and found a quasi-closed-form solution. Total cost is minimized with the optimum level of decision variables. The globality of the decision is proved by the Hessian matrix. Results prove that the total cost is minimized even though the optimum solutions are obtained in quasi-closed-form. A numerical example is elaborated to test the validity of the model numerically and lastly clarify the comparison among SSSD, SSMD, and SSMUD policies.

Published
Jun 29, 2020
How to Cite
SANGAL, Isha et al. A JOINT INVENTORY MODEL WITH RELIABILITY, CARBON EMISSION, AND INSPECTION ERRORS IN A DEFECTIVE PRODUCTION SYSTEM. Yugoslav Journal of Operations Research, [S.l.], v. 30, n. 3, p. 381-398, june 2020. ISSN 2334-6043. Available at: <http://yujor.fon.bg.ac.rs/index.php/yujor/article/view/862>. Date accessed: 26 apr. 2024.
Section
Articles