• Journal of Internet Computing and Services
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• v.18 no.1
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• pp.121-129
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• 2017

Demand forecasting is one of the most critical tasks in defense logistics, because the failure of the task can bring about a huge waste of budget. Up to date, ROK-MND(Republic of Korea - Ministry of National Defense) has analyzed past component consumption data with time-series techniques to predict each component's demand. However, the accuracy of the prediction still needs to be improved. In our study, we attempted to find consumption pattern using data mining techniques. We gathered an 18,476 component consumption data first, and then derived diverse features to utilize them in identification of demanding patterns in the consumption data. The results show that our approach improves demand forecasting with higher accuracy.

• Proceedings of the Korean Reliability Society Conference
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• 2000.11a
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• pp.321-328
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• 2000

본 연구는 새로운 장비체계 도입 시 초기 일정기간 동안 장비의 목표가용도 유지를 위해 필요한 동시조달수리부속(Concurrent Spare Parts)와 적정소요 산출에 관한 해법을 제시한다. 새로운 장비체계 도입 시 함께 보급되는 예비수리부속은 장비체계 운용에 중요한 역할을 한다. 따라서 장비체계가 주어진 임무를 수행하는 동시에 정상상태를 유지하기 위한 적정수준의 예비부속 확보가 필요하며 최소의 비용으로 장비의 가동률을 극대화 할 수 있도록 하여야 한다. 본 연구에서는 부품의 고장특성 및 수리능력을 고려한 고장분포함수를 바탕으로 각 부속별 중요도를 만족시키는 초기 수리부속 소요 결정모형과 해 산정기법을 제시하며 가용예산 제약에 따른 소요조정을 통해 최적의 예비부속 재고수준을 결정한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.05a
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• pp.405-408
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• 2020

국방분야에서 전력 운영유지를 위한 군수분야 운영 효율화는 매우 중요한 이슈이다. 군수분야의 효율성을 위해 적정한 수리부속 확보는 장비의 가동률과 예산 절감 차원에서 중요성이 크다. 이에 군은 다양한 기법을 활용하여 수리부속 수요예측에 대한 노력을 계속해 왔으나, 여전히 예측 정확도 향상을 위한 지속적인 노력이 요구된다. 이에 본 연구에서는 지난 9개년의 수리부속 수요데이터를 분석하고 다양한 머신러닝을 활용하여 예측정확도를 비교·분석하고, 가장 적합한 수리부속 수요예측 모델을 제안한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.234-241
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• 2021

By recognizing the importance of demand forecasting, the military is conducting many studies to improve the prediction accuracy for repair parts. Demand forecasting for repair parts is becoming a very important factor in budgeting and equipment availability. On the other hand, the demand for intermittent repair parts that have not constant sizes and intervals with the time series model currently used in the military is difficult to predict. This paper proposes a method to improve the prediction accuracy for intermittent repair parts of the Patriot. The authors collected intermittent repair parts data by classifying the demand types of 701 repair parts from 2013 to 2019. The temperature and operating time identified as external factors that can affect the failure were selected as input variables. The prediction accuracy was measured using both time series models and data mining models. As a result, the prediction accuracy of the data mining models was higher than that of the time series models, and the multilayer perceptron model showed the best performance.

• Journal of the Korea Society for Simulation
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• v.21 no.3
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• pp.79-88
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• 2012

Recently, the study in efficient operation, maintenance, and equipment-design have been growing rapidly in military industry to meet the required missions. Through out these studies, the importance of Concurrent Spare Parts(CSP) are emphasized. The CSP, which is critical to the operation and maintenance to enhance the availability, is offered together when a equipment is delivered. Despite its significance, th responsibility for determining the range and depth of CSP are done from administrative decision rather than engineering analysis. The purpose of the paper is to optimize the number of CSP per item using simulation and multiple regression. First, the result, as the change of operational availability, was gained from changing the number of change in simulation model. Second, mathematical regression was computed from the input and output data, and the number of CSP was optimized by multiple regression and linear programming; the constraint condition is the cost for optimization. The advantage of this study is to respond with the transition of constraint condition quickly. The cost per item is consistently altered in the development state of equipment. The speed of analysis, that simulation method is continuously performed whenever constraint condition is repeatedly altered, would be down. Therefore, this study is suitable for real development environment. In the future, the study based on the above concept improves the accuracy of optimization by the technical progress of multiple regression.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.8
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• pp.5260-5266
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• 2015

To develop weapon system, Concurrent Spare Parts(CSP) is one of the important somethings in terms of Intergrated Logistics System(ILS). CSP is very important to improve the availability of weapon system, and various research about CSP are performed. However, most of the research does not consider the effects between sub-item's failure and weapon system's multiple function. In other words, if sub-item's failure does not seriously influence weapon system's specific function, the point, not necessarily to replace sub-item, is not considered. Therefore, the method to calculate CSP based on above consideration is written by failure-function matrix in this paper. The study follows the procedure below. First, it's to define the operation and maintenance procedure of weapon system. Second, failure-function matrix is developed. Third, simulation model is desinged by input data. Finally, The quantity of CSP is calculated by simulation and evolution strategy, meta-model. This study suggests new research direction to calculate CSP.

• Journal of the Korea Society for Simulation
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• v.22 no.1
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• pp.31-40
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• 2013

Recent development in science and technology has modernized the weapon systems of ROKN (Republic Of Korea Navy). Although the cost of purchasing, operating, and maintaining the cutting-edge weapon systems has been increased significantly, the national defense expenditure is under a tight budget constraint. In order to maintain the availability of ships with low cost, we need an efficient and scientific method for managing repairable parts. In this study, we propose a simulation model that computes the availability of ship's repairable parts. Our model is based on the METRIC (Multi Echelon Technique Repairable Item Control) model and extends to five sub-models to reflect the realistic situations that arise in the navy, such as planned maintenance, condemnation, lateral transshipment, and cannibalization. We have performed simulations to compute the availability of repairable parts while setting the part-level consistent throughout the five models and carried out two sensitivity analyses. The simulation results show the differences in the part availability in different models. The experiments confirm our claim that ROKN needs an inventory management system that captures the operational characteristics of the navy.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.4893-4901
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• 2013

In order for a machine, especially used in the defense industry, to consistently operate during its life-time, lots of study has been done in machine design as well as machine maintenance. However, the realistic study is necessary in management and operation of a military support facility, where spare parts are stored and retrieved. In this paper, efficient arrangement of spare parts are proposed to acquire increased in efficiency and decreased in cost for operation management of the military support facility. First, spare parts is assorted by MTBF(Mean Time Between Failure) and divided in to three groups A/B/C as an alternative arrangement. Each defined alternatives will go under simulations and RULA(Rapid Upper Limb Assessment), which is posture classification scheme evaluation attributes, to find working time and posture difficulty and lastly by entropy measurement to be selected. This research proposes the efficient spare parts arrangement in military support facility to minimize working time and posture difficulty. By taking system and human engineering approach together into consideration, it will lead to show a specific value.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.4
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• pp.101-109
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• 2018

In order to predict the future needs of the aircraft repair parts, each military group develops and applies various techniques to their characteristics. However, the aircraft and the equipped weapon systems are becoming increasingly advanced, and there is a problem in improving the hit rate by applying the existing demand prediction technique due to the change of the aircraft condition according to the long term operation of the aircraft. In this study, we propose a new prediction model based on the conventional time-series analysis technique to improve the prediction accuracy of aircraft repair parts by using machine learning model. And we show the most effective predictive method by demonstrating the change of hit rate based on actual data.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.162-163
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• 1999