Effective cost minimization strategy and an optimization model of a reliable global supply chain system

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Authors
Daehy, Yahya H.
Krishnan, Krishna K.
Alsaadi, Ahmed K.
Alghamdi, Saleh Yahya
Issue Date
2019
Type
Article
Language
en_US
Keywords
Minimum cost , Reliability optimization , Reliability rate , Supply chain system
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Abstract

Attributable to high competition in global manufacturing market and outsourcing suppliers, many supply chain systems have become more complex and faced with high risks and low performance. Many financial losses and failures are likely to be due to risks among supply chain's components. As a prescription to improve quality, performance, and profitability of the supply chain, companies would like to measure and optimize the reliability of the entire supply chain system. Also, companies are interested in minimizing the cost of processes and improvement throughout the supply chain system. This paper explains a statistical method that measures the reliability rate of each part in the system as well as the entire supply chain. Moreover, the paper elucidates a mathematical model that improves the reliability of the supply chain through minimization of cost components. The results and findings of this study confirm that the proposed model can be applied to improve the supply chain system. Also, the system can be improved to reach a designed reliability rate as given target to the model. The illustrated methodology can be used as a guide on how to develop a reliable supply chain system plan with low possible costs. © 2019 by the authors; licensee Growing Science, Canada.

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© 2019 by the authors; licensee Growing Science, Canada. This is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
Citation
Daehy, Yahya H.; Krishnan, Krishna K.; Alsaadi, Ahmed K.; Alghamdi, Saleh Y. 2019. Effective cost minimization strategy and an optimization model of a reliable global supply chain system. Uncertain Supply Chain Management, vol. 7:no. 3:pp 381-398
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Growing Science
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ISSN
2291-6822
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