TY - JOUR
T1 - Impact of random defective rate on lot size focusing work-in-process inventory in manufacturing system
AU - Kang, Chang Wook
AU - Ullah, Misbah
AU - Sarkar, Biswajit
AU - Hussain, Iftikhar
AU - Akhtar, Rehman
N1 - Publisher Copyright:
© 2016 Informa UK Limited, trading as Taylor & Francis Group.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/3/19
Y1 - 2017/3/19
N2 - Literature has focused inventory models with intensive emphasis on imperfect production processes in recent past. However, the work-in-process-based inventory models have been ignored, relatively, in general and the impact of random defects in the form of reworkable and non-reworkable defect rate on lot size and total cost function in particular. This paper develops mathematical models for work-in-process-based inventory by incorporating the effect of random defects rate on lot size and expected total cost function. Our proposed models assume that defective products produced during the production process follow random distributions. Defective products, either in the form of reworkable or rejected production units, follow four types of distribution density functions: uniform, triangular, double triangular and beta distribution. Mathematical models are derived for optimum lot size based on minimization of expected total cost function through the analytical optimization approach. Numerical examples and detailed sensitivity analysis are carried to illustrate and compare the proposed models at different levels of distribution functions’ parameters.
AB - Literature has focused inventory models with intensive emphasis on imperfect production processes in recent past. However, the work-in-process-based inventory models have been ignored, relatively, in general and the impact of random defects in the form of reworkable and non-reworkable defect rate on lot size and total cost function in particular. This paper develops mathematical models for work-in-process-based inventory by incorporating the effect of random defects rate on lot size and expected total cost function. Our proposed models assume that defective products produced during the production process follow random distributions. Defective products, either in the form of reworkable or rejected production units, follow four types of distribution density functions: uniform, triangular, double triangular and beta distribution. Mathematical models are derived for optimum lot size based on minimization of expected total cost function through the analytical optimization approach. Numerical examples and detailed sensitivity analysis are carried to illustrate and compare the proposed models at different levels of distribution functions’ parameters.
UR - http://www.scopus.com/inward/record.url?scp=84989855225&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84989855225&partnerID=8YFLogxK
U2 - 10.1080/00207543.2016.1235295
DO - 10.1080/00207543.2016.1235295
M3 - Article
AN - SCOPUS:84989855225
VL - 55
SP - 1748
EP - 1766
JO - International Journal of Production Research
JF - International Journal of Production Research
SN - 0020-7543
IS - 6
ER -