• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.5
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• pp.705-715
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• 2019

The purpose of this study is to analyze the necessity of organizing an exclusive unit to perform the division Engineering Reconnaissance, and how to organize exclusive unit. To this end, first, it was analyzed whether exclusive unit organization was necessary by using organization-conditions and AHP. Next, through ARENA model simulation and task-analysis, it was determined how many people would be organized, and how the class structure would be appropriate. As a result, first, it is reasonable to organize the Engineering Reconnaissance unit as an exclusive unit, and the best way is to organize all-time(war/peace time). Second, the exclusive unit should be organized into a total of 10 persons(2~3 cadres, 7~8 soldiers). We hope that the research will contribute to the rational procedure of our military unit structure organization and set the standards for applying the quantitative methodology.

• Journal of Biosystems Engineering
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• v.34 no.5
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• pp.342-350
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• 2009

Currently TMR feed produced in commercial plant is one of the major source to feed cattle for both beef and dairy farm. However, because of lack of cutting and mixing system for utilizing domestic produced firmly baled round roughage in commercial TMR plant, these commercial TMR feed can not satisfy to farmers both in quality and price points of view. In order to solve these problems, a farm group size TMR plant model was developed in this study. The model plant was consist of round bale receiving and cutting system, pneumatic conveying system for transfer the roughage which was cut at the cutter to TMR mixer through pneumatic conveyor, TMR mixer enable to soften the stiff rice strew and to mix with other ingredients, finished feed bin which can be transfer to either packing system or individual farm, packing system by tycon bag which contains 400 kg unit and bulk unloading system to individual farmer. Also, a simulation model ARENA was applied to the model system in order to evaluate and check the production rate in each unit process and operation rate of total system and to find out if there are any clogged unit system obstructing the smooth flow of the total process flow. Processing cycle for produce one batch of the model plant was less than 30 minutes. Thus, it will take less than four hours for producing 16 tons per day equivalent to 1,000 beef cattle's daily feed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.2
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• pp.76-84
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• 2011

To meet the needs of customer, manufacturing companies are diversifying product making methods. In order to adapt to changes, companies are trying to find a new manufacturing system. In this research, MTS (Make to Stock) and MTO (Make to Order) production methods are simulated using ARENA and the results are compared and analyzed to find a better system. As a result, by combining the advantages of MTS and MTO system, a hybrid production system is developed. The hybrid model is analyzed to verify that it is better than the existing two models, which is MTS and MTO model. The statistic results of output analyzer show that a new system helped to increase production rate and decrease work in process inventory. The hybrid model proved that it contains the merits of MTO production method and MTS production method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.102-109
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• 2018

This paper seeks to present a multi-control method that can contribute to effective control of the production line with multiple bottleneck processes. The multi-control method is the production system that complements shortcomings of CONWIP and DBR, and it is designed to determine the raw material input according to the WIP level of two bottleneck processes and WIP level of total process. The effectiveness of the production system developed by applying the multi-control method was verified by the following three procedures. Raw material input conditions of the multi-control method are as follows. First, raw materials are go into the production line when the number of the total process WIP is lower than established number of WIP in total process and first process is idle. Second, raw materials are introduced when the number of WIP of two bottleneck processes is lower than the established number of WIP of each bottleneck process. Third, raw materials are introduced when the first process and in front of bottleneck process are idle even if the number of WIP in the total process is less than established number of WIP of the total process. The production line with two bottleneck processes was selected as the condition for production environment, and the production process modeling of CONWIP, DBR and multi-control production method was defined according to the production condition. And the optimum limited WIP level suitable for each system was obtained by applying a genetic algorithm to determine the total limited number of WIP of CONWIP, the limited number of WIP of DBR bottleneck process, the number of WIP in the total process of multi-control method and the limited number of WIP of bottleneck process. The limited number of WIP of CONWIP, DBR and multi-control method obtained by the genetic algorithm were applied to ARENA modeling, which is simulation software, and a simulation was conducted to derive result values on the basis of three criteria such as production volume, lead time and number of goods in-progress.