An application of a smart production system to control deteriorated inventory

¹ Department of Mathematics & Statistics, Banasthali Vidyapith, Rajasthan 304022, India
² Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Sinchon-dong, Seodaemun-gu, Seoul 03722, South Korea
³ Sheoraphuli Surendranath Vidyaniketan for Girls High School, Sheoraphuli, Hooghly 712223, India
⁴ Center for Global Health Research, Saveetha Medical College, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu 600077, India
⁵ Department of Industrial and Management Engineering, Pohang University of Science and Technology, 77 Cheongam-ro, Nam-gu, Pohang-si, Gyeongsangbuk-do 37673, South Korea

^* Corresponding author: mitalisarkar.ms@gmail.com

Received: 21 October 2021
Accepted: 30 March 2023

Abstract

Deteriorating products require different handling procedures. Handling procedures includes prevention of the natural deterioration rate of the product. The production of deteriorating products requires prevention technology for those products to use for a long time. Overproduction of deteriorating types of products causes more trouble in preventing deterioration. This study uses a smart production system to control the production of deteriorating products. A controllable production rate controls the production of deteriorating products, and preservation technology reduces the deterioration rate of products. Preservation technology helps extend the life of products, but it requires a specific temperature controlled environment to work at maximum efficiency. Transportation of these products uses refrigerated transportation to maintain the quality during the transportation time. The purpose of using all these features for deteriorating products is to reduce the deterioration rate, which helps to reduce waste generation from production. Besides, imperfect products from the production system pass through a remanufacturing process to support the waste reduction process. A sustainable supply chain management model under the above-stated strategies is described here. Classical optimization is used to find the global optimum solution of the objective function. Then, the total cost of the supply chain is optimized using unique solutions of production rate, number of deliveries, delivery lot size, system reliability, and preservation investment. Global optimum solutions are established theoretically, and few propositions are developed. Some special cases, case studies, and a comparison graph are provided to validate the results. The beta distribution provides the minimum total cost of the system than uniform, gamma, triangular, and double triangular distribution. Smart production allows 72% system reliability with negligible imperfect products. Besides, the proposed policy gains 22.72% more profit than the existing literature. The model is more realistic through convex 3D graphs, sensitivity analyses, and managerial insights.