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research article

Optimization of sample size and order size in an inventory model with quality inspection and return of defective items

Cheikhrouhou, Naoufel  
•
Sarkar, Biswajit
•
Ganguly, Baishakhi
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December 1, 2018
Annals Of Operations Research

To ensure all products as perfect, inspection is essential, even though it is not possible to inspect all products after producing them like some special type products as plastic joint for the water pipe. In this direction, this paper develops an inventory model with lot inspection policy. With the help of lot inspection, all products need not to be verified still the retailer can decide the quality of products during inspection. If retailer founds products as imperfect quality, the products are sent back to supplier. As it is lot inspection, mis-clarification errors (Type-I error and Type-II error) are introduced to model the problem. Two possible cases are discussed for sending back products as defective lots are immediately withdrawn from the system and send back to supplier with retailer's payment and for second case, retailer sends defective products during receiving next lot from supplier with supplier's investment, like in food industry or in hygiene product industry. The model is solved analytically and results indicate that optimal order size and sample size are intrinsically linked and maximize the total profit. Numerical examples, graphical representations, and sensitivity analysis are given to illustrate the model. The results suggest that sending defective products maintaining the first case is the more profitable than the second case.

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Type
research article
DOI
10.1007/s10479-017-2511-6
Web of Science ID

WOS:000451052000007

Author(s)
Cheikhrouhou, Naoufel  
Sarkar, Biswajit
Ganguly, Baishakhi
Malik, Asif Iqbal
Batista, Rafael
Lee, Young Hae
Date Issued

2018-12-01

Publisher

SPRINGER

Published in
Annals Of Operations Research
Volume

271

Issue

2

Start page

445

End page

467

Subjects

Operations Research & Management Science

•

Operations Research & Management Science

•

production

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imperfect quality

•

sampling inspection

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inspection errors

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nonlinear optimization

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production quantity model

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setup cost reduction

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eoq model

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imperfect quality

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production system

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backorders

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errors

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rework

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deterioration

•

improvement

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LGPP  
Available on Infoscience
December 13, 2018
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/152590
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