Inventory control by using Fuzzy set theory An Applied Research at the Baghdad Soft Drinks Company

Authors

  • وقاص سعد خلف
  • عبد الله باسم جاسم

DOI:

https://doi.org/10.33095/jeas.v23i101.170

Keywords:

: Fuzzy Time Series, Fuzzy Inference System, The rules of condition and result (If-Then Rules), Fuzzy Set Theory, Production Model Without Shortage, Purchase Model Without Shortage

Abstract

The production companies in the Iraqi industry environment facing many of the problems related to the management of inventory and control In particular in determining the quantities inventory that should be hold it. Because these companies  adoption on personal experience and some simple mathematical methods which lead to the identification of inappropriate quantities of inventory.

       This research aims to identify the economic quantity of production and purchase for the Pepsi can 330ml and essential components in Baghdad soft drinks Company in an environment dominated by cases of non ensure and High fluctuating as a result of fluctuating demand volumes and costs associated with inventory, and has been using the fuzzy time series method to dispose of uncertainty and fluctuation accompanying demand for finished product , and using the fuzzy inference system (If-Then Rules) to remove the cases of uncertainty associated with the holding inventory cost for the finished product and essential components.

      After removing the fuzzy of demand and holding inventory cost Parameters, been used the production model without Shortage to determine the economic production quantity for the Pepsi can 330 ml, and the purchase model without Shortage to determine the economic order quantity for the product components. The statistical programs (Matlab, Win Qsb.v2) were used for mathematical and statistical analyzes.

 

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Published

2017-12-01

Issue

Section

Managerial Researches

How to Cite

“Inventory control by using Fuzzy set theory An Applied Research at the Baghdad Soft Drinks Company” (2017) Journal of Economics and Administrative Sciences, 23(101), p. 72. doi:10.33095/jeas.v23i101.170.

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