• Journal of the Korea Society for Simulation
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• v.22 no.1
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• pp.31-40
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• 2013

Recent development in science and technology has modernized the weapon systems of ROKN (Republic Of Korea Navy). Although the cost of purchasing, operating, and maintaining the cutting-edge weapon systems has been increased significantly, the national defense expenditure is under a tight budget constraint. In order to maintain the availability of ships with low cost, we need an efficient and scientific method for managing repairable parts. In this study, we propose a simulation model that computes the availability of ship's repairable parts. Our model is based on the METRIC (Multi Echelon Technique Repairable Item Control) model and extends to five sub-models to reflect the realistic situations that arise in the navy, such as planned maintenance, condemnation, lateral transshipment, and cannibalization. We have performed simulations to compute the availability of repairable parts while setting the part-level consistent throughout the five models and carried out two sensitivity analyses. The simulation results show the differences in the part availability in different models. The experiments confirm our claim that ROKN needs an inventory management system that captures the operational characteristics of the navy.

• Management Science and Financial Engineering
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• v.4 no.2
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• pp.15-42
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• 1998

A joint problem of order delivery, setup reduction, and cost-sharing in a two-echelon inventory system in which a vendor supplies multiple products to a group of buyers is studied here. The basic premise is that buyers have independently implemented setup reduction programs to acquire benefits from small order sizes. Doing so, however, causes the buyers' individually optimal order cycles to be differ from that of the vendor. In conjunction with this, two models are considered. In the first model, a multi-buyers single product situation is considered in which the vendor implements a joint supply cycle policy. However, buyers, as the dominant party, insist after implementing the individually optimal setup reduction that the vendor accept their individually optimal order schedules. In the second model. a multi-products, single buyer situation is considered in which the buyer implements a joint order policy. Here, the vendor, as the dominant party, refuses to cooperate fully with the buyer's individually reduced joint order schedule, and designs his own individually optimal setup reduction mix for each product under a given budget constraint. This led to a study of an integrated Setup Reduction/Break-even Pricing Policy for each situation to eliminate mismatches in individually optimal cycle times.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.715-722
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• 2005

Disassembly scheduling is the problem of determining the quantity and timing of disassembling used products while satisfying the demand of their parts or components over a planning horizon. The case of single product type with assembly structure is considered for the objective of minimizing the sum of disassembly operation and inventory holding costs. In particular, the resource capacity constraint is explicitly considered. The problem is formulated as an integer programming model, and a two-stage heuristic with construction and improvement algorithms is suggested in this paper. To show the performance of the heuristic, computational experiments are done on a number of randomly generated problems, and the test results show that the algorithm can give near optimal solutions within a very short amount of computation time.

• Journal of Korean Institute of Industrial Engineers
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• v.26 no.1
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• pp.17-26
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• 2000

This paper presents an integrated order scheduling method with the improved DRP concept for multi-echelon distribution system that has the constraint of limited production capacity of producers. The proposed method reflects the dynamic characteristics of inventory level changes in the regional and central distribution center. The simulation is done with two models : the traditional DRP method and the proposed method presented in this paper. From the results, the latter is more efficient than the former in cost, customer's service level as well as balanced production load on each producer.

• Industrial Engineering and Management Systems
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• v.6 no.2
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• pp.106-118
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• 2007

This paper present a new optimization model to generate aggregate production planning by considering electric cost. The new Time Of Switching (TOS) electric type is introduced by switching over Time Of Day (TOD) and Time Of Use (TOU) electric types to minimize the electric cost. The fuzzy demand and Dynamic inventory tracking with multiple plant capacity are modeled to cover the uncertain demand of customer. The constraint for minimum hour limitation of plant running per one start up event is introduced to minimize plants idle time. Furthermore; the Optimal Weight Moving Average Factor for customer demand forecasting is introduced by monthly factors to reduce forecasting error. Application is illustrated for multiple cement mill plants. The mathematical model was formulated in spreadsheet format. Then the spreadsheet-solver technique was used as a tool to solve the model. A simulation running on part of the system in a test for six months shows the optimal solution could save 60% of the actual cost.

• Journal of the Korea Safety Management & Science
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• v.8 no.5
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• pp.139-150
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• 2006

The aim of this study is to establish an efficient distribution planning for a capacitated multi-stage supply chain. We assume that the demand information during planning horizon is given a deterministic form using a certain forecasting method. Under such a condition, we present a cost effective heuristic method for minimizing chain-wide supply chain inventory cost that is the sum of holding and backorder costs by using look-ahead technique. We cope with the capacity restriction constraints through look-ahead technique that considers not only the current demand information but also future demand information. To evaluate performance of the proposed heuristic method, we compared it with the extant research that utilizes echelon stock concept, under various supply chain settings.

• Journal of the Korea Society for Simulation
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• v.29 no.2
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• pp.83-93
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• 2020

Bivariate measure of risk and error(BMORE) plot is originally designed to depict bivariate output data and related statistics obtained from a stochastic simulation such as sample mean, median, outliers, and a boundary of a certain percentile of simulation data. When compared to the static numbers, the plot has a big advantage in visualization that enables scholars and practitioners to understand the potential variability and risk in the simulation data. In this study, beyond just the construction of the plot to depict the variability of a certain system, we add a chance constraint to the plot and apply it for decision making such as checking the feasibility of systems, comparing performances of the systems on statistical background, and also analyzing the sensitivity of the problem parameters. In order to demonstrate an application of the plot, we employ an inventory management problem as an example. However, the techniques and algorithms suggested in this paper can be applied to any other problems comparing systems on bivariate performance measures with simulation/experiment results.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.40-48
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• 2009

In this article, scheduling of a casting sequence is studied in a casting foundry which must deliver products according to the Just-in-time(JIT) production policy of a customer. When a foundry manufactures a variety of casts with an identical alloy simultaneously, it frequently faces the task of production scheduling. An optimal casting schedule should be emphasized in order to maximize the production rate and raw material efficiency under the constraints of limited resources; melting furnaces and operation time for a casting machine. To solve this practical problem-fulfilling the objectives of casting the assigned mixed orders for the highest raw material efficiency in a way specified by the customer's JIT schedule, we implement simple integer programming. A simulation to solve a real production problem in a typical casting plant proves that the proposed method provides a feasible solution with a high accuracy for a complex, multi-variable and multi-constraint optimization problem. Employing this simple methodology, a casting foundry having an automated casting machine can produce a mixed order of casts with a maximum furnace utilization within the due date, and provide them according to their customer's JIT inventory policy.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.6
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• pp.714-723
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• 1999

This paper presents a short-term scheduling algorithm for the operation of steelmaking processes. The scope of the problem covers refining of the hot iron transferred form a blast furnace, ladle treatment, continuous casting, hot-rolling, and coiling for the final products that should satisfy the given demand. The processing time at each unit depends on how much the batch amount is treated, and te dedicated intermediate storage with finite capacity between the units is considered. Resource constraints and initial amount of each state are incorporated into the presented scheduling model for the algorithm of on-line scheduling. We propose amixed integer linear programming (MILP) model with two objectives for the scheduling. The first is to maximize the total profit while atisfying the due date constraint for each product. And the second is to minimize the total processing time, makespan, while satisfying the demand for each product. Especially, we observe the effect of penalizing the intermediate storage and the inventory level of the final product on the scheduling results.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.8-13
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• 2021

The purpose of this study is to propose a throughput costing as a performance measurement tool to measure cost indicators, which are one of the indicators for evaluating organizational performance in a smart factory manufacturing environment. An empirical study by questionnaire was conducted, and 60 experts were surveyed to verify the hypothesis. As a result of the study, it was concluded that the information provided based on throughput costing is helpful in cost measurement and in evaluating organizational performance efficiency and effectiveness, and it was confirmed that this method has usefulness to support the planning and control process. It is proposed that the use of throughput costing by constraint theory, which can maximize throughput and optimize inventory levels in the manufacturing process, can find solutions to bottlenecks affecting the efficiency and effectiveness of organizational performance.