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Growing Science » International Journal of Industrial Engineering Computations » An integrated single-vendor single-buyer production-inventory model for items with imperfect quality and inspection errors

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International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 3 Issue 5 pp. 703-720 , 2012

An integrated single-vendor single-buyer production-inventory model for items with imperfect quality and inspection errors Pages 703-720 Right click to download the paper Download PDF

Authors: J.T. Hsu, L.F. Hsu

DOI: 10.5267/j.ijiec.2012.04.004

Keywords: EOQ, Imperfect quality, Misclassification errors, Supply chain

Abstract: In this paper, we develop an integrated vendor-buyer production-inventory model for items with imperfect quality and inspection errors. The production process is imperfect and produces a certain number of defective items with a known probability density function. We consider the policy in which the delivery quantity to the buyer is identical at each shipment. Once the buyer receives the lot, a 100% screening process of the lot is conducted, and the screening process and demand proceed simultaneously. The screening process is not perfect. The inspector may incorrectly classify a non-defective item as defective, or incorrectly classify a defective item as non-defective. The expected integrated total annual cost of the vendor and the buyer is derived and a solution procedure is provided to find the optimal solution. Numerical examples show that the integrated model gives an impressive cost reduction in comparison to an independent decision by the buyer.

How to cite this paper
Hsu, J & Hsu, L. (2012). An integrated single-vendor single-buyer production-inventory model for items with imperfect quality and inspection errors.International Journal of Industrial Engineering Computations , 3(5), 703-720.

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Journal: International Journal of Industrial Engineering Computations | Year: 2012 | Volume: 3 | Issue: 5 | Views: 9829 | Reviews: 0

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