• 산업공학
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• 제21권4호
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• pp.354-364
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• 2008

This paper deals with a design problem of simulation for MIME (multi indenture and multi echelon) with lateral transshipment. Especially, we consider lateral transshipments in case that (S-1, S) ordering policy is used in multi echelon repair system. Some rules for ordering spare parts in lateral transshipments between the lowest-level units are studied and are implemented by an activity diagram in object-oriented method. By numerical examples, we compare regular (S-1, S) ordering policy and (S-1, S) policy with lateral transshipment.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2006년도 추계 학술대회
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• pp.133-138
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• 2006

The problem that we address is to determine the inventory stockage levels in a multi-echelon inventory system for repairable items in a multi-indenture system. We propose the simulation optimization approach to determine the stockage levels at each echelon, where a simulator for the underlying system is combined with an appropriate optimization tool, Genetic Algorithm (GA).

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 2006년도 추계 학술대회
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• pp.145-150
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• 2006

In terms of that modem equipment become expensive, sophisticated and huge, the cost of developing the equipment is much considered in ILS. Therefore, the model of the level of repair analysis about equipment which have the multi-echelon and multi-indenture are purposed to derive optimal repair policy which mostly satisfy the availability by using the Mixed Integer Programming within the minimum cost.

• 품질경영학회지
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• 제36권2호
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• pp.9-19
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• 2008

Spare part problem of MIME (Multi Indenture Multi Echelon) system under availability constraint has been studied for several decades. In most of existing studies, it was very difficult to obtain the optimal numbers of spare parts and some approximate methods were proposed under many restrictions. In this paper, we consider a simulation to estimate the total cost rate and system availability and a genetic algorithm to obtain the optimal numbers of spare parts. Some numerical examples are also studied.

• 시스템엔지니어링학술지
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• 제12권2호
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• pp.47-57
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• 2016

As the inventory costs of repairable items in military logistics continue to increase, many studies for optimal inventory level of these items are being carried out in advanced countries, including the US, to reduce these costs. Research on inventory level optimization for repairable items aimed to achieve the availability goal of a system with a MIME(Multi Indenture Multi Echelon) repair policy structure first began with Sherbrooke's METRIC and developed into various types. This research is to analyze and compare recent V-METRIC related studies to search for another variation in this field. This paper mainly looks at how to determine optimum inventory level for each repairable item to achieve a specific availability target within a limited budget, and also how to minimize inventory cost while achieving its availability target by determining optimal inventory level of each repairable item.

• 경영과학
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• 제31권3호
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• pp.61-76
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• 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.

• 경영과학
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• 제26권1호
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• pp.209-223
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• 2009

In this paper, an analysis problem of repair levels and spare part allocation for MIME(Multi indenture multi echelon) systems is studied using simulation and meta-heuristics. We suggest a method to determine simultaneously repair levels and spare parts allocation to minimize the life cycle cost of MIME system under availability constraint. A simulated annealing method is used to analyze the repair levels and genetic algorithm is used to obtain the optimal allocation of spare parts. We also develop a simulation system to calculate the life cycle cost and system availability. Some numerical examples are also studied.

• 시스템엔지니어링학술지
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• 제13권1호
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• pp.79-88
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• 2017

For the PBL contract, it is necessary for the contracting parties to share information regarding the reasonable inventory-level and the cost of its repair parts for the estimated demand. There are various models which can be used for this purpose. Among them, V-METRIC model is considered to be the most efficient and is most frequently applied. However, this model is usually used for optimizing the inventory level of the repair parts of the system under operation. The model uses a time series forecast model to determine the demand rate, which is a mandatory input factor for the model, based on past field data. However, since the system at the deployment stage has no operational performance record, it is necessary to find another alternative to be used as the demand rate of the model application. This research applies the V-METRIC model to find the optimal inventory level and cost estimation for repairable items to meet the target operational availability, which is a key performance indicator, at the time of the PBL contract for the deployment system. This study uses the calculated value based on the allocated MTBF to the system as the demand rate, which is used as input data for the model. Also, we would like to examine changes in inventory level and cost according to the changes in target operational availability and MTBF allocation.