• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.271-277
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• 1999

In this paper, a case study is introduced on the development of an inventory management system for the textile industry. For the low-cost and high-efficient production, a systematic management is needed from make-to-order to delivery. In this paper, an integrated inventory management system for the D company is developed to manage the whole information related with make-to-order, production, delivery, and inventory, and so forth.

• Journal of Korean Society for Quality Management
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• v.16 no.1
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• pp.78-87
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• 1988

The purpose of this study is to develop the algorithm applicable to the integrated production inventory model under quantity discount. To achieve this purpose, the integrated production inventory model which unifies the inventory problem of raw materials and the finished product for a single product manufacturing system is considered. The product is manufactured in batches and the raw materials are obtained from outside suppliers but some of the raw materials are discounted according to the purchasing quantity. The intergrated production inventory problem considered in this study is formulated by the non-linear mixed integer programming model, and the optimal solution is obtained by using the algorithm developed by Goyal. Then, the algorithm developed by this study is applied to the quantity discount problem, and the optimal solution is revised by this results. The quantity discount algorithm of the integrated production inventory model developed by this study gives a systematic procedure to obtain the optimum policy to minimize the total cost in any case. The numerical example involving 20 raw materials and 5 raw materials among them are discounted according to the purchasing quantity is given to verify the mathematical model and the algorithm developed in this study.

• Journal of the Korea Safety Management & Science
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• v.16 no.2
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• pp.131-138
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• 2014

Auto part industry supplies production for auto manufacturer and after market. These company have inventory for delivery. High inventory level can be good for delivery, but cost will be increase. Low inventory level can be customer unsatisfaction for delivery late. Low inventory level also is reason of low productivity by decreasing product batch size. These article suggest model for calculation a proper inventory level and prove a effect by simulation of some company.

• Journal of the Korean Operations Research and Management Science Society
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• v.37 no.2
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• pp.45-56
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• 2012

This paper considers a supply chain consisting of a component manufacturer and a product manufacturer. The component manufacturer provides components for the product manufacturer based on a vendor-managed inventory type of supply contract, and also faces demands from the market with the option of to accept or reject each incoming demand. Using the Markov decision process model, we examine the structure of the optimal production control and inventory rationing policy. Two types of heuristics are presented. One is the fixed-buffer policy and the other uses two linear functions. We implement a computational study and present managerial insights based on the observations.

• Journal of the Korean Operations Research and Management Science Society
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• v.30 no.2
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• pp.117-129
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• 2005

This paper considers a make-to-order inventory-production system in which customer orders are admitted only when the number of outstanding customer orders is below a value committed by the system. We deal with general distributions for the customer order Inter-arrival, production, and replenishment lead time processes. Monotonicities of the optimal average cost with respect to these distribution parameters are established using sample path coupling arguments. When distributions are given as an exponential one, we implement a sensitivity analysis on the optimal inventory policy and show that it has monotonicities with respect to system costs using dynamic programming.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.59-65
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• 1988

This paper discusses the problem of coordinating aggregate planning and production schedules, minimizing the combined set-up inventory and capacity costs. In this study, by using the relation of fixed production quantity and the number of set-up we develop a heuristirc procedure of solving the discrete demand, fixed production quantity, variable capacity problem. First, we obtain the trade-off between set-up cost and capacity cost, then search the point minimizing the combined inventory and capacity costs.

• Journal of the Korea Institute of Building Construction
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• v.5 no.4 s.18
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• pp.153-164
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• 2005

This study aims at establishing JIT production management system to enable manage the resources input into from procurement through construction based on correct identification of the process, an analysis on the amount of input materials and information sharing. This study has focused on the process control and working process of rebar work in domestic apartment house construction where the overall scope of Process from the planning phase to the construction phase has been analyzed in this study. Also construction phase was selected for the application of a sample case. A basic model for JIT production was generated with these processes. Furthermore A questionnaire and the on-site survey with process, checklist and control data were prepared and performed for the application of JIT production management model into rebar work. The governing scopes of JIT production management system include process management, material management, yard loading and moving management and inventory control, and the operation of each control item

• Journal of the Korean Operations Research and Management Science Society
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• v.1 no.1
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• pp.151-170
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• 1976

There are many cases of production processes which intermittently produce several different kinds of products for stock through one set of physical facility. In this case, an important question is what size of production run should be prduced once we do set-up for a product in order to minimize the total cost, that is, the sum of the set-up, carrying, and stock-out costs. This problem is used to be called scheduling of multiple products through a single facility in the production management field. Despite the very common occurrence of this type of production process, no one has yet devised a method for determining the optimal production schedule. The purpose of this study is to develop quantitative analytical models which can be used practically and give us rational production schedules. The study is to show improved models with application to a can-manufacturing plant. In this thesis the economic production quantity (EPQ) model was used as a basic model to develop quantitative analytical models for this scheduling problem and two cases, one with stock-out cost, the other without stock-out cost, were taken into consideration. The first analytical model was developed for the scheduling of products through a single facility. In this model we calculate No, the optimal number of production runs per year, minimizing the total annual cost above all. Next we calculate No$_{i}$ is significantly different from No, some manipulation of the schedule can be made by trial and error in order to try to fit the product into the basic (No schedule either more or less frequently as dictated by) No$_{i}$, But this trial and error schedule is thought of inefficient. The second analytical model was developed by reinterpretation by reinterpretation of the calculating process of the economic production quantity model. In this model we obtained two relationships, one of which is the relationship between optimal number of set-ups for the ith item and optimal total number of set-ups, the other is the relationship between optimal average inventory investment for the ith item and optimal total average inventory investment. From these relationships we can determine how much average inventory investment per year would be required if a rational policy based on m No set-ups per year for m products were followed and, alternatively, how many set-ups per year would be required if a rational policy were followed which required an established total average inventory inventory investment. We also learned the relationship between the number of set-ups and the average inventory investment takes the form of a hyperbola. But, there is no reason to say that the first analytical model is superior to the second analytical model. It can be said that the first model is useful for a basic production schedule. On the other hand, the second model is efficient to get an improved production schedule, in a sense of reducing the total cost. Another merit of the second model is that, unlike the first model where we have to know all the inventory costs for each product, we can obtain an improved production schedule with unknown inventory costs. The application of these quantitative analytical models to PoHang can-manufacturing plants shows this point.int.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.1-7
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• 2003

This paper considers an Integrated one-vendor multi-buyer production-inventory model where the vendor manufactures multiple products In lot at Her associated finite production rates In the model. It is allowed for earth product to be shipped In lot to the buyers before the whole product production is not completed yet. Each product lot is dispatched to the associated buyer In a number or shipments. The buyers consume their products at fixed rates. The objective is to the production and shipment schedules in the Integrated system. which minimizes the mean total annual cost per unit time. The mean total annual cost consists or production setup cost inventory holding cost and shipment cost. For the model, an Iterative optimal solution procedure with shipment consolidation policy incorporated is derived. It is then tested through numerical experiments to show how efficient and effective He shipment consolidation policy is.

• Journal of Korean Institute of Industrial Engineers
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• v.34 no.1
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• pp.1-12
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• 2008

The Kanban system in Just-In-Time (JIT) production is very effective in reducing the inventories when consumption rate of the final product is relatively stable. When large fluctuations exist in the consumption rate, a new production ordering policy in which the production order quantity is determined by smoothing the demands exponentially is more suitable. This new ordering policy has not been investigated sufficiently. In this research, a multi-stage production and inventory system with stock points for materials and finished items located at each stage is considered. Approximations of average inventories at each stage in the system are derived theoretically. Numerical simulations are carried out to assess the accuracy of approximations and to evaluate the effectiveness of the new ordering policy as compared with the Kanban system. As a result, it is shown that the new ordering policy can achieve significantly lower inventory costs than the original Kanban system. The new ordering policy thus emerges as a key concept for an effective supply chain management.