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http://dx.doi.org/10.9766/KIMST.2018.21.4.529

Demand Forecast of Spare Parts for Low Consumption with Unclear Pattern  

Park, Min-Kyu (Department of Industrial Management Engineering, Korea University)
Baek, Jun-Geol (Department of Industrial Management Engineering, Korea University)
Publication Information
Journal of the Korea Institute of Military Science and Technology / v.21, no.4, 2018 , pp. 529-540 More about this Journal
Abstract
As the equipment of the military has recently become more sophisticated and expensive, the cost of purchasing spare parts is also steadily increasing. Therefore, demand forecast accuracy is also becoming an issue for the effective execution of the spare parts budget. This study predicts the demand by using the data of spare parts consumption of the KF-16C fighter which is being operated in the Republic of Korea Air Force. In this paper, SARIMA(Seasonal Autoregressive Integrated Moving Average) is applied to seasonal data after dividing the spare parts consumptions into seasonal data and non-seasonal data. Proposing new methods, Majority Voting and Hybrid Method, to the non-seasonal data which consists of spare parts of low consumption with unclear pattern, We want to prove that the demand forecast accuracy of spare parts improves.
Keywords
Spare Parts; Majority Voting; Hybrid Method; Demand Forecast Accuracy; Low Consumption with Unclear Pattern;
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Times Cited By KSCI : 1  (Citation Analysis)
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