Sustainable inventory management with hybrid production system and investment to reduce defects

Jauhari, Wakhid Ahmad; Pujawan, I Nyoman; Suef, Mokh

doi:10.1007/s10479-022-04666-8

Cited by 16 publications

(1 citation statement)

References 54 publications

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“…Again, Sana 52 developed an imperfect production inventory model considering buffer stock during preventive maintenance policy. On the same year, Jauhari et al 53,54 developed various production inventory models considering imperfect production. Recently, Ali et al, 24 Manna et al, 25 Raiya and Mittal, 55 Das et al, 44 developed various production inventory systems considering imperfect production.…”

Section: Literature Reviewmentioning

confidence: 99%

Impact of emission and service constraint for an imperfect production system under two level Hamiltonian

Das

Ali

Shaikh

et al. 2023

Optim Control Appl Methods

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Considering the impact of emission on environment, over the last few decades, reduction of emission during production process (or emission free production process) appears to be one of the most growing preferences for every manufacturing firm. Again, manufacturing companies of different products are bounded to offer various facilities to their consumers in order to survive in the current highly competitive market situation. Primarily considering these two factors taken in to account, this study addresses an imperfect manufacturing inventory model in which customers' demand increases linearly w. r. to emission reduction level, service level from the manufacturer and decreases nonlinearly w. r. to price of the items. The analytical expressions of production rates, emission levels and service levels are derived by solving a number of optimum control problems using Hamiltonian maximum principle with a values for the business period and selling price. The basic goal is to maximize the average profit of the system. In addition, a number of numerical examples are considered to elaborate four distinct instances involved in the proposed model and these are solved numerically using teaching learning based optimization algorithm. Finally, sensitivity experiment is performed to investigate the influence of various system factors on the best‐found policies. The sensitivity analysis indicates that service rate provided by the manufacturer and selling price of the items impose a huge impact on the average profit of the system. Further, the carbon reduction affects the revenue of the system less significantly.

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