• Journal of the Korean Society of Industry Convergence
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• v.26 no.5
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• pp.855-866
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• 2023

With the rapid advancement and sophistication of defense weapon systems, the government, military, and the defense industry have conducted various innovative attempts to improve the efficiency of post-logistics support(PLS). The Ministry of Defense has mandated RAM-C(Reliability, Availability, and Maintainability-Cost) analysis as a requirement according to revised Total Life Cycle System Management Code of Practice in May 2022. Especially, for the project budget forecast of new PBL(Performance Based Logistics) business contacts, RAM-C is recognized as an obligatory factor. However, relevant entities have not officially provided guidelines or manuals for RAM-C analysis, and each defense contractor conducts RAM-C analysis with different standards and methods to win PBL-related business contract. Hence, this study aims to contribute to the generalization of the analysis procedure by presenting a cost analysis case based on RAM-C for the supply of military depot maintenance PBL project. This study presents formulas and procedures to determine requirements of military depot maintenance PBL project for repair parts supply. Moreover, a sensitivity analysis was conducted to find the optimal cost/utilization ratio. During the process, a correlation was found between supply delay and total cost of ownership as well as between cost variability and utilization rate. The analysis results are expected to provide an important basis for the conceptualization of the cost analysis for the supply of military depot maintenance PBL project and are capable of proposing the optimal utilization rate in relation to cost.

• Journal of Service Research and Studies
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• v.6 no.4
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• pp.75-85
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• 2016

Coal can be divided into thermal coal and coking coal. The price of thermal coal is basically affected by demand and supply. However, many other factors with regard to economic condition such as exchange rate, economy growth rate also make an influence on the price. This study is targeted to develop a forecast model for thermal coal price by using System Dynamics Method. System dynamics provides results that better reflect the real world by employing an inter-dependent system of variables. This study found out that 8 factors have important influence on the thermal coal price. Most of the data of the variables were acquired from the Bloomberg Database. The period extends to 2 years and 4 months, from May of 2011 to August of 2013. The causal relations among the variables were acquired by regression analysis

• Journal of Korea Port Economic Association
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• v.33 no.1
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• pp.75-87
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• 2017

The purpose of this study is to utilize the system dynamics to carry out a medium and long-term forecasting analysis of the bunker price. In order to secure accurate bunker price forecast, a quantitative analysis was established based on the casual loop diagram between various variables that affects bunker price. Based on various configuration variables such as crude oil price which affects crude oil consumption & production, GDP and exchange rate which influences economic changes and freight rate which is decided by supply and demand in shipping and logistic market were used in accordance with System Dynamics to forecast bunker price and then objectivity was verified through MAPEs. Based on the result of this study, bunker price is expected to rise until 2029 compared to 2016 but it will not be near the surge sighted in 2012. This study holds value in two ways. First, it supports shipping companies to efficiently manage its fleet, offering comprehensive bunker price risk management by presenting structural relationship between various variables affecting bunker price. Second, rational result derived from bunker price forecast by utilizing dynamic casual loop between various variables.

• Environmental and Resource Economics Review
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• v.28 no.2
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• pp.177-200
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• 2019

Energy demand forecast which serves as an essential input in energy policy is exposed to multiple factors of uncertainty such as GDP and weather forecast uncertainty. The Master Plan of Electricity Market in Korea which is biennially prepared is critically based on fluctuating energy demand forecast whereas its resulting proposal on electricity generation mix is substantially irreversible. The paper provides a real options model to evaluate energy transition policy by considering Knightian uncertainty as a measure to study multiple uncertainties with multiple set of probability distributions. Our finding is that the current energy transition policy under the master plan is not robust in terms of securing stable management of electricity demand and supply system.

• Plant Journal
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• v.15 no.1
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• pp.31-37
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• 2019

In this study, to improve the accuracy of forecast of heat demand in the district heating system, this study applied heat demand performance among the main factors of district heating demand forecast in Pankyo area as the heat sales information of the user facility instead of existing heat source facility heat supply information, and compared the existing method with the accuracy based on the actual value. As a result of comparing the difference of the forecasts values of the existing and changed methods based on the performance values over the one week (2018.01.08 ~ 01.14) during the hot water peak, the relative error decreased from 7% to 3% The relative error between the existing and revised forecasts was 9% and 4%, respectively, for the five-month cumulative heat demand from February to February 2018, Also, in case of the weekend where the demand of heat is differentiated, the relative error of the forecasts value is consistently reduced from 10% to 5%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.10
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• pp.4812-4818
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• 2013

This paper contains material of the supply-demand forecasting of solar salt for food in Korea. The solar salt was granted admission for food by the act of salt management in 2007. So, the yearly statistics of solar salt for food are not enough to forecast the supply-demand unsing econometrics. However, the related industry become interested in market size of the solar salt for food and the growth potential of the market. This study deal with the supply-demand forecasting of solar salt for food in light of industry of solar salt, consumption trends, export-import quantity, etc. This research results indicate that the production quantity will be 222-384 thousand MT, the export quantity will be 498-565 thousand MT, the export quantity will be 2.67-3.62 thousand MT, the consumption quantity will be 767-996 thousand MT.

• Journal of Information Technology Applications and Management
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• v.15 no.3
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• pp.79-90
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• 2008

With the corporate environment nowadays being surrounded by plenty of information, the sharing of information among businesses through mutual cooperation tops the list of hot issues. Predictions of demands from the customer, business, or consumer by sharing information can affect the inventory and order production system. However, notwithstanding the importance of sharing information, empirical studies on quantitative use of information still remain insufficient in spite of many a discussion now being made on the sharing of information. This paper proposes to examine the ways meteorological information may affect the rises in the achievements of supply chains in distributive businesses, the kind of information that noticeably affects the consumer behavioral patterns in the distributive businesses but rarely perceived as a form of information shared by businesses. This study is based on a model in which meteorological information has been added as the one used to predict demands, after the beer distribution game has been modified to fit the current status, and simulations under an assumptive situation, where decisions are made on a daily basis, were conducted 50 times for a period of 1000 days for the generalization of the results, while at the same time a Duncan Test was conducted to determine the threshold to use the meteorological information that will be most profitable to the retailer, wholesaler, supplier and the supply chain as a whole. Our findings indicate that corporations have thresholds that vary from business to business depending upon the ratio of backlog costs to inventory costs. At the same time, our findings also show that there existed effective thresholds depending upon the ratio of backlog costs to inventory costs for the performance of the overall supply chain.

• Journal of Korean Society of Forest Science
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• v.97 no.4
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• pp.458-466
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• 2008

This study was carried out to forecast long-term supply and demand of chestnut and to analyze the impacts of change in the environment of domestic and international chestnut markets. For these ends, the study developed a partial equilibrium market model, in which in-shelled chestnut market was vertically linked to shelled chestnut market. To examine the predictive ability of the model for the endogenous variables ex-post simulation was run for the period 1990 through 2003. In general, all endogenous variables reproduced the historical trends during the period except for disuse areas and newly established areas. The results of forecasting supply and demand show that domestic in-shelled chestnut production is estimated to decrease slightly from 76,447 ton in 2005 to 76,286 ton in 2020 and that exports of shelled chestnut continue to be decreased.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.6959-6968
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• 2015

This study aims to update the supply-demand model of wood products(FOSMO-2013) and to forecast mid and long run supply and demand for each products. The subjects of the study include sawnwood, plywood, particle board, fiberboard(MDF), and pulp. The updated partial equilibrium model is composed of supply function, import demand function, demand function, price relation function. The long run outlooks of world prices of wood and wood products are imported from the results of Buongiorno(2012). This study also adopt Buongiorno's scenarios, which includes three scenarios of IPCC(A1B, A2, B2) and the other one with assumption of increasing fuelwood consumption of A1B scenario. The result says that the domestic productions of wood products are expecting to decrease while the imports of them increase even there are some differences among the products as well as scenarios.

• Journal of Korean Society of Water and Wastewater
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• v.25 no.4
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• pp.581-589
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• 2011

Generally, treated water or raw water is transported into storage reservoirs which are receiving facilities of local governments from multi-regional water supply systems. A water supply control and operation center is operated not only to manage the water facilities more economically and efficiently but also to mitigate the shortage of water resources due to the increase in water consumption. To achieve the goal, important information such as the flow-rate in the systems, water levels of storage reservoirs or tanks, and pump-operation schedule should be considered based on the resonable water demand forecasting. However, it is difficult to acquire the pattern of water demand used in local government, since the operating information is not shared between multi-regional and local water systems. The pattern of water demand is irregular and unpredictable. Also, additional changes such as an abrupt accident and frequent changes of electric power rates could occur. Consequently, it is not easy to forecast accurate water demands. Therefore, it is necessary to introduce a short-term water demands forecasting and to develop an application of the forecasting models. In this study, the forecasting simulator for water demand is developed based on mathematical and neural network methods as linear and non-linear models to implement the optimal water demands forecasting. It is shown that MLP(Multi-Layered Perceptron) and ANFIS(Adaptive Neuro-Fuzzy Inference System) can be applied to obtain better forecasting results in multi-regional water supply systems with a large scale and local water supply systems with small or medium scale than conventional methods, respectively.