• Korean Management Science Review
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• v.28 no.1
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• pp.117-127
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• 2011

In the Multi-Echelon maintenance environment, METRIC(Multi-Echelon Technique for Repairable Item Control) has been used in several different inventory level selection models, such as MOD-METRIC, Vari-METRIC, and Dyna- ETRIC. While this model's logic is easy to be implemented, a critical assumption of infinite maintenance capacity would deteriorate actual values, especially Expected Back Order(EBO)s for each item. To improve the accuracy of EBO, we develop two models using simulation and queueing theory that calculates EBO considering finite capacity. The result of our numerical example shows that the expected backorder from our model is much closer to the true value than the one from Vari-METRIC. The queueing model is preferable to the simulation model regarding the computational time.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.3
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• pp.226-232
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• 2001

This paper presents an efficient method for the problem of determining the spare inventory level of a multi-echelon repairable-item inventory system. We consider the system with two levels of inventory, two levels of service and with a general service time distribution. We propose an algorithm that determines the spare inventory level to satisfy the minimum fill rate with the minimum cost. Experimental results show that the algorithm is accurate and efficient.

• Journal of the Korea Safety Management & Science
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• v.16 no.4
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• pp.323-330
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• 2014

Various inventory control theories have tried to modelling and analyzing supply chains by using quantitative methods and characterization of optimal control policies. However, despite of various efforts in this research filed, the existing models cannot afford to be applied to the realistic problems. The most unrealistic assumption for these models is customer demand. Most of previous researches assume that the customer demand is stationary with a known distribution, whereas, in reality, the customer demand is not known a priori and changes over time. In this paper, we propose a reinforcement learning based adaptive echelon base-stock inventory control policy for a multi-stage, serial supply chain with non-stationary customer demand under the service level constraint. Using various simulation experiments, we prove that the proposed inventory control policy can meet the target service level quite well under various experimental environments.

• Journal of the Korea Safety Management & Science
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• v.11 no.3
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• pp.139-148
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• 2009

In a real-life supply chain environment, demand forecasting is usually represented by probabilistic distributions due to the uncertainty inherent in customer demands. However, the customer demand used for an actual supply chain planning is a single deterministic value for each of periods. In this paper we study the choice of single demand value among of the given customer demand distribution for a period to be used in the supply chain planning. This paper considers distributed multi-echelon supply chain and the objective function of this paper is to minimize the total costs, that is the sum of holding and backorder costs over the distribution network under the service level constraint, by using demand selection scheme. Some useful findings are derived from various simulation-based experiments.

• IE interfaces
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• v.11 no.2
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• pp.13-24
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• 1998

A distribution system is composed of multiple levels from a producer to customers, and it's objective is to supply customers with goods timely with a prescribed level of quality at a minimum cost. For the installation and operation of multi-echelon distribution system, DRP(Distribution Resource Planning) is widely used. However, because of the characteristic difference of material flow dynamic of each distribution center, it is almost impossible to get the optimal distribution scheduling. In this paper, an improved DRP method to schedule multi-echelon distribution network is proposed so that the lot-size and order point is dynamically obtained to meet the change of demand rate and timing. The experiment is done with various demand pattern, forecast errors of demand and lead times of central distribution center. The proposed method is compared with traditional statistical approach.

• Journal of Biosystems Engineering
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• v.35 no.3
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• pp.197-205
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• 2010

An automatic echelon feeder of brown rice was presented for quality inspection system using color image processing. A echelon feeder was developed with vibratory feeder and cylindrical indent singulator having oblique light. The vibratory feeder consisted of a hopper, electromagnetic vibrator and multichannel grooves and supply the grain sample to the singulator. The feeding performance such as feed rate, blocking frequency of the channel was dependent on the size of groove and vibration pattern. A cylindrical indent singulator consisted of a rotating cylinder, prisms and a tungsten-halogen light source. It delivered grain kernels under the camera in a echelon form and illuminate the kernels with oblique ray and ambient light. The size of the indents installed on the surface of the rotating cylinder was determined by the dimensions of the paddy and a small triangular prism was placed in each indent to apply $ 20^{\circ}$ oblique light to the grain kernel.

• Journal of Korean Institute of Industrial Engineers
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• v.21 no.3
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• pp.313-327
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• 1995

This paper deals with ordering policies for a multi-echelon distribution system. The system we are concerned consists of one Central Distribution Center(CDC) and N nonidentical Regional Distribution Centers(RDCs) which have different demand rates, minimum filtrates, leadtimes, etc. We develop an algorithm for determining the optimal ordering policies of the CDC and the RDCs under the constraints of minimum filtrates of RDCs and maximum allowable delay of CDC.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1990.04a
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• pp.222-244
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• 1990

A multi-echelon structure of manufacturing and distribution system in considered, where the raw materials are transformed into a finished good through a number to manufacturing echelons and it is distributed to the lower echelons(retailers, or customers). The raw material, work-in-process, finished good inventory and the distribution costs are unified into one model. The objective is to determine the ordering policy of raw materials, manufacturing lot size, the number of sub-batch and the distribution policy of the finished good which minimize the annual total system cost. A computer program for a heuristic search technique is developed, by which a numerical example is examined.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.113-120
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• 1995

Much of the past work regarding repairable item stockage has concentrated on the development of models and policies for systems in steady state. However, there are important situations in which the transient behavior is most important. A dramatic example of this is the potential dynamic behavior exhibited by demands and service in the deployment of an Air Force squadron at the onset of a conflict. The purpose of this paper is to derive some probability distributions necessary for providing an integrated approach for a multi-echelon inventory system with nonstationary demands and service rates.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.10a
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• pp.566-569
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• 2004

본 연구에서는 생산능력의 제한이 있는 다계층(multi-echelon) 공급사슬에서의 효과적인 분배계획수립을 목적으로 한다. 수요 정보는 계획 기간(planning horizon) 동안 확정적인 형태로 주어지고 이러한 상황 하에서 전체 공급사슬에서 발생하는 재고유지 비용(holding cost)과 재고이월 비용(backorder cost)의 합을 최소화하는 분배 문제의 해법을 제시하고자 한다. 본 연구에서는 총비용을 최소화하는 각 노드별 분배량을 결정하기 위해서 look-ahead 기법을 사용한다. Look-ahead 기법을 통해 분배 계획 수립 시 해당 기간의 수요 정보뿐만 아니라 미래 수요를 함께 반영함으로써 생산능력 제한에 효과적으로 대처할 수 있도록 하였다. Look-ahead 기법을 적용하기 위해 본 문제를 단일 기계 일정계획(single machine scheduling) 문제로 전환하고 이에 대한 효율적인 발견적 기법을 제시한다. 또한 제안된 발견적 기법의 성능을 평가하기 위해 다양한 실험 조건하에서 제안된 알고리듬과 기존의 미래 수요를 고려하지 않는 계층 재고 정책(echelon stock policy)의 결과를 비교하여 본 연구의 우수성을 입증하였다.