Impact of random defective rate on lot size focusing work-in-process inventory in manufacturing system
Chang Wook Kang,
Misbah Ullah,
Biswajit Sarkar,
Iftikhar Hussain and
Rehman Akhtar
International Journal of Production Research, 2017, vol. 55, issue 6, 1748-1766
Abstract:
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.
Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (12)
Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2016.1235295 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:55:y:2017:i:6:p:1748-1766
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20
DOI: 10.1080/00207543.2016.1235295
Access Statistics for this article
International Journal of Production Research is currently edited by Professor A. Dolgui
More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().