• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.09a
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• pp.379-386
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• 2002

The objective of this study is to investigate the seismic demand on the isolated slab-on-steel girder bridge under cold climate conditions. To this end comparative test results are presented of laminated elastomeric and lead-rubber seismic isolators in warm and cold temperature conditions. At extremely cold temperatures, rubber "glass-harden" and as a result rubber bearings that may be used for seating bridges behave in a significantly non-linear fashion. From the nonlinear time history analysis of the isolated slab-on-steel girder bridge, larger forces are transferred to the substructures. however smaller displacement at superstructure is obtained under cold climate conditions. These phenomenons might need to be considered in design stage of the seismically isolated bridges.

• Industrial Engineering and Management Systems
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• v.12 no.2
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• pp.85-94
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• 2013

This research investigates the supply chain contract between a distributor and a supplier in which the selling period is relatively short in comparison with long production lead time. At the first stage, supplier who is a Stackelberg leader offers the distributor a contract with a set of parameters, and subjected to those parameters, the distributor places the number of initial orders as well as options. In order to purchase the option, the distributor pays non-linear option premium price with respect to the number of purchased options. At the second stage, based on realized demand, the distributor has the right to exercise option as either put or call which is limited up to the number of purchased options. The wholesale price contract is used as a benchmarking contract. This research has confirmed that the supply chain contract with a non-linear option premium price can help to coordinate the supply chain.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.5
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• pp.694-702
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• 2014

One of the most important devices in an underwater vessel is a propulsion system. It should be a quiet and efficient system for stealthy operations in the large mission area. Hence lead-acid battery system has been used to supply the energy to electric motor. Recent technological developments and improvements, such as polymer electrolyte membrane(PEM) fuel cell and lithium polymer battery and have created the potential to improve overall power and propulsion performance. An underwater vessel always starts their mission with a limited energy and is not easy to refuel. Therefore design of energy elements, such as fuel cell and battery, and their load distribution are important to increase the maximum operating time of underwater vessel. In this paper, the lead-acid battery/PEM fuel cell and lithium polymer battery/PEM fuel cell were suggested as propulsion system and their performances were analyzed by modeling and simulation using Matlab/Simulink. Each model concentrated on representing the characteristics of energy element depending on demand current. As a result the effect of load distribution between battery and fuel cell was evaluated and the operation time of each propulsion system was able to be estimated exactly.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.1-6
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• 2011

This paper describes the issue of batch scheduling.In food production, the lead-time from produc-tion to sale should be decreased becausefreshness of the product is important. Products are shipped at diverse times depending on a demand of sellers, because the types of sellers has become diversified such as super-markets, convenience stores and etc. production of quantity demanded must be completed by time to ship it then. The authors consider a problem with due-dates constraints and construct the algorithm to find the opti-mal schedule that satisfy the due-dates constraint, batch size constraint, inventory time constraint and mini-mize total flow time.

• Proceedings of the Safety Management and Science Conference
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• 2002.05a
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• pp.115-120
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• 2002

Today's environment of enterprise is changing. They have to face customer' demands with the right product, the right service and supply them at the right time. And also cut down logistics and inventory cost and bring up the profit as much as they can. This means the change of putting enterprise first in importance to putting customer first importance. therefore to correspond to customer's demand, shorting lead time is becoming a essential condition. The answer to this changes of environment is supply chain management. In this paper, It consolidates the necessity on a LTV(Life Time Value) and analyzes data which is concerned of Customer Value. Under the these environments, defines the LTV(Life Time Value) rule that can improve the customer value.

• Journal of the Korea Safety Management & Science
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• v.4 no.3
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• pp.131-140
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• 2002

Today's environment of enterprise is changing, They have to face customer' demands with the right product, the right service and supply them at the right time. And also cut down logistics and inventory cost and bring up the profit as much as they can. This means the change of putting enterprise first in importance to putting customer first importance. therefore to correspond to customer's demand, shorting lead time is becoming a essential condition. The answer to this changes of environment is supply chain management. In this paper, It consolidates the necessity on a LTV(Life Time Value) and analyzes data which is concerned of Customer Value. Under the these environments, defines the LTV(Life Time Value) rule that can improve the customer value. We solved this problems using AHP(Analytic Hierarchy Process) for consistency at relationship matrix, AHP(Analytic Hierarchy Process) is based on Saaty's consistency rate. If consistency rate is under 0.1 point, preference rate's weights are acceptable. This study develop a program for AHP weights and support Satty's consistency rate.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.2
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• pp.266-272
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• 2011

Real Time Pricing(RTP) is used not only to stabilize the price volatility in electricity market, but to hedge the price risk for Load Serving Entity(LSE). This paper presents an efficient method to reduce the risk of the price volatility in real-time electricity market. For designing the RTP, load patterns of customer are calculated by applying the demand elasticity and customer's utility is also analyzed to compute the RTP revenue through the risk-attribute of the LSE. In the end, the distribution of the LSE's profits can be evaluated to lead the optimal RTP value, depending on the level of customer's participation. Results from the case study based on PJM data are reported to illustrate the proposed method.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.151-171
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• 2015

This study examined the concepts of the Internet of Things(IoT), the major issue and IoT trend in the domestic and international market. also reviewed the advent of IoT era which caused a 'Paradigm Shift'. This study proposed a solution for the appropriate corresponding strategy in terms of Enterprise. Global competition began in the IoT market. So, Businesses to be competitive and responsive, the government's efforts, as well as the efforts of companies themselves is needed. In particular, in order to cope with the dynamic environment appropriately, faster and more efficient strategy is required. In other words, proposed a management strategy that can respond the IoT competitive era on tipping point through the vision of paradigm shift. We forecasted and proposed the emergence of paradigm shift through a comparative analysis of past management paradigm and IoT management paradigm as follow; I) Knowledge & learning oriented management, II) Technology & innovation oriented management, III) Demand driven management, IV) Global collaboration management. The Knowledge & learning oriented management paradigm is expected to be a new management paradigm due to the development of IT technology development and information processing technology. In addition to the rapid development such as IT infrastructure and processing of data, storage, knowledge sharing and learning has become more important. Currently Hardware-oriented management paradigm will be changed to the software-oriented paradigm. In particular, the software and platform market is a key component of the IoT ecosystem, has been estimated to be led by Technology & innovation oriented management. In 2011, Gartner announced the concept of "Demand-Driven Value Networks(DDVN)", DDVN emphasizes value of the whole of the network. Therefore, Demand driven management paradigm is creating demand for advanced process, not the process corresponding to the demand simply. Global collaboration management paradigm create the value creation through the fusion between technology, between countries, between industries. In particular, cooperation between enterprises that has financial resources and brand power and venture companies with creative ideas and technical will generate positive synergies. Through this, The large enterprises and small companies that can be win-win environment would be built. Cope with the a paradigm shift and to establish a management strategy of Enterprise process, this study utilized the 'RTE cyclone model' which proposed by Gartner. RTE concept consists of three stages, Lead, Operate, Manage. The Lead stage is utilizing capital to strengthen the business competitiveness. This stages has the goal of linking to external stimuli strategy development, also Execute the business strategy of the company for capital and investment activities and environmental changes. Manege stage is to respond appropriately to threats and internalize the goals of the enterprise. Operate stage proceeds to action for increasing the efficiency of the services across the enterprise, also achieve the integration and simplification of the process, with real-time data capture. RTE(Real Time Enterprise) concept has the value for practical use with the management strategy. Appropriately applied in this study, we propose a 'IoT-RTE Cyclone model' which emphasizes the agility of the enterprise. In addition, based on the real-time monitoring, analysis, act through IT and IoT technology. 'IoT-RTE Cyclone model' that could integrate the business processes of the enterprise each sector and support the overall service. therefore the model be used as an effective response strategy for Enterprise. In particular, IoT-RTE Cyclone Model is to respond to external events, waste elements are removed according to the process is repeated. Therefore, it is possible to model the operation of the process more efficient and agile. This IoT-RTE Cyclone Model can be used as an effective response strategy of the enterprise in terms of IoT era of rapidly changing because it supports the overall service of the enterprise. When this model leverages a collaborative system among enterprises it expects breakthrough cost savings through competitiveness, global lead time, minimizing duplication.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.10
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• pp.1390-1396
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• 2013

The paper estimated the reasonable market price of lead-acid battery energy storage system (BESS) intended for demand management of electricity customers. As time-of-use (TOU) tariffs have extended to a larger number of customers and gaps in the peak and off-peak rates have gradually risen, deployment of BESS has been highly needed. However, immature engineering techniques, lack of field experiences and high initial investment cost have been barriers to opening up ESS markets. This paper assessed electricity cost that BESS operation could save for customers and, based on the possible cost savings, estimated reasonable prices at which BESSs could become a more prospective option for demand management of customers. Battery scheduling was optimized to maximize the electricity cost savings that BESS would possibly achieve under TOU tariffs conditions. Basic economic factors such as payback period and return on investment were calculated to determine reasonable market prices. Actual load data of 12 industrial customers were used for case studies.