Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/64422
Title: A stochastic production-inventory model in a two-state production system with inventory deteriorating product, rework process and backordering
Authors: Li, N
Chan, FTS 
Chung, SH 
Tai, AH
Keywords: Rtochastic
Backordering
Economic production quantity (EPQ)
Inventory deterioration
Rework
Issue Date: 2015
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE transactions on systems, man, and cybernetics. Systems, v. PP, no. 99, p. 1-11 How to cite?
Journal: IEEE transactions on systems, man, and cybernetics. Systems 
Abstract: The existing economic production quantity (EPQ) models in imperfect production systems normally assume either deteriorating production processes or deteriorating inventory. In this paper, the two aspects are combined together in a single approach to solve single machine, single product EPQ problem. There are assumed to be two states: 1) in-control and 2) out-of-control state. At the beginning of each production cycle, the production process is in control with a low defective rate. After a certain time period, the production process switches from an in-control to an out-of-control state. As a result, the defect rate increases to another level and more defective items are produced. Defective products are reworked after the normal production process all together but before that they are stored in an inventory, so a corresponding inventory holding cost is generated. Backordering is also considered in this model and products are first used to satisfy the backlog demand in each production run. Three different cases are considered and discussed in which the switch of state occurs in the backlog period, the inventory surplus period, and after the normal production period, respectively. By finding the optimal total production and backlog quantity, the expected total cost per unit product is minimized.
URI: http://hdl.handle.net/10397/64422
ISSN: 2168-2216
EISSN: 2168-2232
DOI: 10.1109/TSMC.2016.2523802
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