• Journal of the military operations research society of Korea
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• v.33 no.1
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• pp.19-29
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• 2007

This study deals with developing and operating Reliability Analysis & Evaluation System for aircraft parts by analyzing ROKAF's AMMIS and phase inspection data for optimal inspection frequency. We suggest operating model with improving and adjusting inspection cycle by analyzing failure time data and tendency of crack with RELEX and Minitab software.

• Proceedings of the Military Operations Research Society of Korea Conference
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• 2007.03a
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• pp.75-102
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• 2007

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.1
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• pp.77-83
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• 2010

In this paper, we proposed new outworn aircraft management procedure. ROKAF has both good management skill and information system, AMMIS, regarding aircraft maintenance based on all kinds of aircraft's defects. To optimize and secure aircraft's operation, management of the outworn aircraft is very important for ROKAF. With respect to these outworn aircraft's defects and maintenance, we analyzed defects occurrence pattern of outworn aircraft by using AMMIS data and Market Basket Analysis, and found the specified association rules for each defect. By using these association rules, we developed new management procedure for outworn aircraft based on the results of affinity analysis. The management procedure in this paper will also be used to optimal operation and maintenance of other aircraft and weapon systems.

• Journal of the military operations research society of Korea
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• v.34 no.2
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• pp.79-101
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• 2008

This study is for improvement of repair part demand forecasting method of Republic of Korea Air Force aircraft. Recently, demand prediction methods are Weighted moving average, Linear moving average, Trend analysis, Simple exponential smoothing, Linear exponential smoothing. But these use fixed weight and moving average range. Also, NORS(Not Operationally Ready upply) is increasing. Recommended method of Box-Jenkins' ARIMA can solve problems of these method and improve estimate accuracy. To compare recent prediction method and ARIMA that use mean squared error(MSE) is reacted sensitively in change of error. ARIMA has high accuracy than existing forecasting method. If apply this method of study in other several Items, can prove demand forecast Capability.