Demand Forecast of Spare Parts for Low Consumption with Unclear Pattern |
Min-Kyu Park, Jun-Geol Baek |
Department of Industrial Management Engineering, Korea University |
적은 소모량과 불분명한 소모패턴을 가진 수리부속의 수요예측 |
박민규, 백준걸 |
고려대학교 산업경영공학과 |
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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. |
Key Words:
Spare Parts, Majority Voting, Hybrid Method, Demand Forecast Accuracy, Low Consumption with Unclear Pattern |
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