• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.449-455
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• 2020

Inventory management is one of the important business functions for manufacturing companies to determine market responsiveness. Customers' needs are diversifying, and the life cycle of products is decreasing, thus increasing the importance of inventory management. However, for small-scale manufacturing companies, investing in an IT system for inventory management is practically difficult. In this study, we introduce an inventory and warehouse management model that can be applied simply and quickly in small-scale manufacturing companies. Firstly, we introduce the concept of the properties of inventory and provide an analytical methodology based on the age and quantity of the inventory. Secondly, in accordance with the properties of the inventory, we introduce location management rules for warehouse operation. To apply the proposed model, we studied a wallpaper manufacturing company and verified the applicability of the proposed methods in the field. The proposed model can be applied immediately as part of on-site improvement activities by small-scale manufacturing companies, and inventory management activities are expected to reduce bad long-term inventory and further secure storage capacity for warehouses.

• Journal of Korean Society for Quality Management
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• v.16 no.2
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• pp.92-98
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• 1988

In this paper a model is developed for an inventory system in which the number of units of acceptable quality in a replenishment lot is uncertain and the demand. during the stockout period is back ordered and. also under the same condition an inventory model with experdited stockout is developed. It is assumed that the fraction of the acceptable quality in a replenishment lot is a random variable whose probability distribution is known. The optimal replenishment policy is synthesized for such a system. A numerical example is used to illustrate the theory.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.31 no.3
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• pp.110-116
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• 2008

Operational strategy for inventory control in the distribution system has been given attention. If an individual enterprise implements the strategy, it is not easy to gain scale merits because of limited quantity or burden of inventory. In this study, we propose an operational strategy for inventory control that considers managerial integration of regional distribution centers (RDCs) and present a model of it. In a network of several RDCs, they could share inventory information and supply parts for others in case of an inventory shortage. And a numerical example of the network is illustrated, which compares two operational strategies, integration management of RDCs and individual management of them. The result shows total cost reduction in the strategy of integration management through the efficient inventory control of multi-echelon distribution.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.2
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• pp.251-256
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• 2006

In this paper we consider multi-stage, multi-product production, inventory systems which have assembly-tree-structure. We propose a new mathematical model for pull type ordering systems based on JIT manufacturing systems. To apply the model to an actual automobile parts manufacturer, the objective of proposed model is to minimize the sum of inventory and setup costs. Finally, a numerical example and computational results are given to illustrate the proposed model.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.19-32
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• 2018

This study focuses on an M/M/1 queue with an attached continuous-type inventory. The customers arrive into the system according to the Poisson process, and are served in their arrival order; i.e., first-come-first-served. The service times are assumed to be independent and identically distributed exponential random variable. At a service completion epoch, the customer consumes a random amount of inventory. The inventory is controlled by the traditional (s, S)-inventory policy with a generally distributed lead time. A customer that arrives during a stock-out period assumed to be lost. For the number of customers and the inventory size, we derive a product-form stationary joint probability distribution and provide some numerical examples. Besides, an operational strategy for the inventory that minimizes the long-term cost will also be discussed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.48
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• pp.37-52
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• 1998

In many distribution systems important cost reductions and/or service improvements may be achieved by adopting an efficient inventory policy and proper selection of facilities. These efficiency improvements and service enhancements clearly require an integrated approach towards various logistical planning functions. The areas of inventory control and transportation planning need to be closely coordinated. The purpose of this paper is to construct an integrated model that can minimize the total cost of the transportation and inventory systems between multiple origin and destination points, where in origin point i has the supply of commodities and in destination point j requires the commodities. In this case, demands of the destination points are assumed random variables which have a known probability distribution. Using the lot-size reorder-point policy and the safety stock level that minimize total cost we find optimal distribution centers which transport the commodities to the destination points and suggest an optimal inventory policy to the selected distribution center. We also show if a demand greater than one unit will occur at a particular time, we describe the approximate optional replenishment policy from computational results of this lot-size reorder-point policy. This model is formulated as a 0-1 nonlinear integer programming problem. To solve the problem, this paper proposes heuristic computational procedures and a computer program with UNIX C language. In the usefulness review, we show the meaning and validity of the proposed model and exhibit the results of a comparison between our approach and the traditional approach, respectively.

• 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.24 no.1
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• pp.127-136
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• 1998

This paper presents a stochastic partial backorder inventory model for the situation in which demand follows normal distribution and back order ratio during that stockout period decreases exponentially according to the length of backorder period. In the paper, an objective function is formulated to minimize the average annual cost, which is the sum of the ordering, carrying, time-proportional backordering, and lost sales cost. And then sensitivity analysis for various exponential backorder ratios and standard deviations of leadtime demand are presented. The inventory model in the paper is reduced to a backorder model and lost sales model, when backorder ratio is 1 and 0, respectively.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.2
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• pp.113-127
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• 2006

We consider an integrated supply chain model in which multiple suppliers replenish items for a single buyer's demand. Also the buyer specifies a basic replenishment cycle and the suppliers replenish the items only at those time intervals. Namely, we propose a model to study and analyze the benefit by coordinating supply chain inventories through the basic replenishment cycle time. The objective of this model is to minimize the total relevant annual cost of the integrated inventory model. After developing proposed coordinated models, we suggest heuristics for searching the solutions of our models. Finally, numerical and computational experiments for each policy are carried out to evaluate the benefits of those models and the compensation policy is addressed to share the benefits.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.11
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• pp.1076-1080
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• 2015

An inventory control system was developed for a distribution system consisting of a single multiproduct warehouse serving a set of customers and purchasing products from multiple vendors. Purchase orders requesting multiple products are delivered to the warehouse in a process. The receipt of customer orders by the warehouse proceeded in order intervals and in order quantities that are subject to random fluctuations. The objective of warehouse operation is to minimize the total cost while maintaining inventory levels within the warehouse capacity by adjusting the purchase order intervals and quantities. An adaptive model predictive control algorithm was developed using a periodic square wave model to represent the material flows. The adaptive concept incorporated a stabilized minimum variance control-type input calculation coupled with input/output stream parameter predictions. The effectiveness of the scheme was demonstrated using simulations.