• 품질경영학회지
• /
• 제24권1호
• /
• pp.44-49
• /
• 1996

This paper deals with a (Q, r) spare-part inventory model with gamma leadtime. In the model, if the inventory level falls to a reorder point r, a replenishment order quantity Q is ordered. Assumming that the number of operating units is one and the lifetime of a unit follows an exponential distribution, we derive the expected cost rate and suggest a procedure to obtain the optimal pair of (Q, r) minimizing the cost rate. A numerical example is presented to explain the model.

• 경영과학
• /
• 제31권2호
• /
• pp.33-48
• /
• 2014

It is important to maintain on operational availability of aircraft during wartime. The KF-16 fighter, the backbone of the ROKAF (Republic Of Korea Air Force), has a single engine. Therefore, the engine has a critical influence on operational availability. The purpose of this study is to estimate optimal levels of spare part inventories concerning both engines and modules. That is provided by linear programming methods utilizing a developed meta-model. For drawing out the meta-model, we develop a simulation model which can consider wartime demands. In the previous study, $2^k$ factorial design method is used to check the influence of each independent variable. That method requires relatively many scenarios because every extreme value combination of independent variables should be checked. However, this study adopts NOLH (Nearly Orthogonal Latin Hypercube) as an experimental design. By adopting NOLH, this study increases not only efficiency but also accuracy. That is proven by comparing the validity of the developed meta-model on both experimental designs. This study also utilizes the OptQuest simulation tool in ARENA to derive the optimal level of spare stocks. By comparing the result of OptQuest to that of the developed meta-model, the validity of this study is secured.

• 경영과학
• /
• 제31권3호
• /
• pp.61-76
• /
• 2014

There are three methods for calculating the optimal level for spare part inventories in a MIME (Multi Indenture and Multi Echelon) system : marginal analysis, Lagrangian relaxation method, and genetic algorithm. However, their solutions are sub-optimal solutions because the MIME system is neither convex nor separable by items. To be more specific, SRUs (Shop Replaceable Units) are required to fix a defected LRU (Line Replaceable Unit) because one LRU consists of several SRUs. Therefore, the level of both SRU and LRU cannot be calculated independently. Based on the limitations of three existing methods, we proposes a improved algorithm applying marginal analysis on determining LRU stock level and genetic algorithm on determining SRU stock level. It can draw optimal combinations on LRUs through separating SRUs. More, genetic algorithm enables to extend the solution search space of a SRU which is restricted in marginal analysis applying greedy algorithm. In the numerical analysis, we compare the performance of three existing methods and the proposed algorithm. The research model guarantees better results than the existing analytical methods. More, the performance variation of the proposed method is relatively low, which means one execution is enough to get the better result.

• 대한조선학회논문집
• /
• 제46권2호
• /
• pp.171-178
• /
• 2009

In this paper, RFID (Radio Frequency Identification) based management system is introduced to control effectively logistic supply items and machinery spare parts in a ship. To apply an RFID system under very harsh environment in a ship which is a steel-structured small area with lots of compartment, we measured reading distances and angles in open space, in an steel compartment, and an real ship separately in order to investigate the reliability between various tags and RFID.

• 한국국방경영분석학회지
• /
• 제1권1호
• /
• pp.131-135
• /
• 1975

One of the pending issues of the Ministry of Defense is the efficient management of space parts for the weapon systems. It has been known that more than 000 million dollars are needed for spare parts for the weapon systems annually. Though the problem demands a serious consideration, there has not been any systematic study on the problem as far as the author knows. One way to approach the problem is through an investigation of the system reliability under constraints. A measure of how well a system performs or meets its design objectives is provided by the concept of system reliability. If successful operation is desired for a specified period of time, reliability is defined as the probability that the system will perform satisfactorily for the required time period. This interpretation of reliability is normally applied to devices which are subject to random failures such as electrical or mechanical systems. It has been found necessary to express system reliability in terms of the reliability of the components or subsystems which comprise the system. The major subsystems of an aircraft, for example, include the electronics, powerplant, airframe and armament subsystems. Therefore, the optimal spare part kit can be found by maximizing the system reliability subject to cost or other constraints.

• 산업경영시스템학회지
• /
• 제20권44호
• /
• pp.123-128
• /
• 1997

A data base design framework for predictive a preventive-maintenance system is presented in this paper in order to effectively control machines and reduce accident rates in the workplace. The data base is designed to meet general management requirements to evaluate different maintenance strategies. There are seven data files: the equipment list maintenace pesonnel, maintenance history, maintenance specification, spare part, maintenance equipment, and maintenance schedules. Each data base file has several record based upon data acquisition.

• 산업공학
• /
• 제19권3호
• /
• pp.245-254
• /
• 2006

Equipments in container terminal have a lot of parts, and an equipment breakdown affects the productivity of terminal. In this paper, we develop a maintenance management system for improving reliability, availability and maintainability of equipments in container terminals. The developed system consists of five modules : equipment structure module, equipment operation management module, maintenance control module, spare part control module and data analysis module. The system supports reliability engineers to manage and improve RAM of equipments in container terminals. For example, FMEA, failure state analysis and life distribution parameters estimation are easily or automatically done by the system. This system also provides optimal preventive maintenance intervals by simulation and optimal yearly PM schedules for equipments in container terminal are recommended.

• 인터넷정보학회논문지
• /
• 제18권1호
• /
• pp.121-129
• /
• 2017

수리부속 수요예측은 장비가동률 향상과 국방 운영 예산 효율화 제고를 위한 국방 군수 분야의 핵심 과제 중 하나이다. 현재 우리군은 수리부속 소요 데이터를 활용한 시계열 기법으로 과거 데이터 분석을 통해 수리부속 수요예측에 활용하고 있으나 정확도 제고에 지속적인 노력이 요구되고 있는 실정이다. 이에 본 연구에서는 지난 5개년의 수리부속 18,476개 품목의 수요데이터를 수집하고 데이터마이닝 기법을 활용한 수리부속 수요예측 모델을 제안하였다. 제안한 모델에 따른 실험 결과는 기존 시계열 기법에 비해 개선된 수요예측 정확도를 보였다.

• 한국시뮬레이션학회논문지
• /
• 제23권3호
• /
• pp.19-25
• /
• 2014

수요예측은 경영 전략을 포함한 모든 경영 활동의 기초가 된다. 특히 부품의 수요예측은 공급망관리 측면에서 매우 중요한 요소 중 하나이다. 부품의 수요는 다양한 산업에서 종종 간헐적 특성을 포함한다. 간헐적 특성이란 수요가 발생하지 않는 경우가 빈번한 현상을 지칭한다. 간헐적 수요 현상에서는 발생된 수요의 분산이 크고 그 발생간격이 확률적이다. 따라서 간헐적 특성을 갖는 수요를 예측하기 위해서 일반적인 시계열 분석기법이나 인과관계를 이용한 모형(회귀모형)을 사용하는 것은 적합하지 않다. 이는 기존의 방법들이 실제 수요행태를 묘사하기 어렵기 때문이다. 이러한 간헐적 수요의 예측을 위해 마코프 부트스트랩이 개발되었다. 이 방법은 1계차 자기상관성을 반영하며 리드타임 동안 수요의 합이 독립임을 가정하였다. 본 연구에서는 리드타임 내 수요 합의 독립가정을 완화한 부트스트랩 방법을 제안한다. 수정된 부트스트랩 방법에 의해 재추출된 데이터는 실측 데이터의 간헐적 특성을 근사적으로 반영한다. 마지막으로 실측 데이터에 수정된 방법을 적용한 예측 결과를 사례로 제시하고자 한다.

• 산업경영시스템학회지
• /
• 제41권1호
• /
• pp.50-58
• /
• 2018

Intermittent demand is a demand with a pattern in which zero demands occur frequently and non-zero demands occur sporadically. This type of demand mainly appears in spare parts with very low demand. Croston's method, which is an initiative intermittent demand forecasting method, estimates the average demand by separately estimating the size of non-zero demands and the interval between non-zero demands. Such smoothing type of forecasting methods can be suitable for mid-term or long-term demand forecasting because those provides the same demand forecasts during the forecasting horizon. However, the smoothing type of forecasting methods aims at short-term forecasting, so the estimated average forecast is a factor to decrease accuracy. In this paper, we propose a forecasting method to improve short-term accuracy by improving Croston's method for intermittent demand forecasting. The proposed forecasting method estimates both the non-zero demand size and the zero demands' interval separately, as in Croston's method, but the forecast at a future period adjusted by binomial weight according to occurrence probability. This serves to improve the accuracy of short-term forecasts. In this paper, we first prove the unbiasedness of the proposed method as an important attribute in forecasting. The performance of the proposed method is compared with those of five existing forecasting methods via eight evaluation criteria. The simulation results show that the proposed forecasting method is superior to other methods in terms of all evaluation criteria in short-term forecasting regardless of average size and dispersion parameter of demands. However, the larger the average demand size and dispersion are, that is, the closer to continuous demand, the less the performance gap with other forecasting methods.