• 대한산업공학회지
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• 제24권4호
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• pp.475-483
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• 1998

Structural changes in an economy system bring about serious problems in establishing economic policies. The boom of middle-east export, the oil shock, and the recent dollar crisis in Korean economy are such examples. Hence, it is necessary to identify and estimate those structural changes. This study focuses on an output and price and analyzes structural changes in aggregate demand and supply. The aggregate demand and supply structures are described by conventional dynamic simultaneous equations model, where each structural change is represented by dummy variables and estimated by the proposed Bayesian method. By applying this model to Korean output and price, structural changes in the aggregate demand and supply are analyzed.

• 대한인간공학회지
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• 제26권1호
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• pp.79-85
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• 2007

Demand forecasting methods for a consumer product such as TV or refrigerator are widely known. However, sales forecast for a brand new product cannot be estimated using conventional forecasting methods. This study proposes a five-step procedure in forecasting a newly developed product. Step one defines functions in a High Touch product in order to estimate relative attraction of the product to consumer group. In step two, for a comparison purpose, a compatible product that is successfully penetrated into market is selected. Step three breaks a target population into many segments based on demography. Step four calculates relative attraction between the High Touch product and the compatible product. Finally, market penetration rate of the High Touch product is estimated using a bell-shaped diffusion curve of the compatible product. The process offers a method to estimate potential demand and growth pattern of the new High Touch product.

• Industrial Engineering and Management Systems
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• 제3권2호
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• pp.129-133
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• 2004

Studies on the optimal location of retail store have been made in case of no obstacle(Minagawa etal. 1999). This paper deals with the location problem of retail store considering obstacles (e.g. rivers, railways, highways, etc.) and obstacle-overcoming points (e.g. bridges, railway crossings, zebra crossings, overpasses, etc.). We assume that (1) commercial goods dealt here are typically convenience goods, (2) the population is granted as potential demand, (3) the apparent demand is a function of the maximum migration length and the distance from the store to customers, (4) the scale of a store is same in every place and (5) there is no competitor. First, we construct the basic model of customers' behavior considering obstacles and obstacle-overcoming points. Analyzing the two dimensional model, the arbitrary force attracting customers is represented as a height of a cone where the retail store is located on the center. Second, we formulate the total demand of customers and determine the optimal location that maximizes the total demand. Finally, the properties of the optimal location are investigated by simulation.

• 산업경영시스템학회지
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• 제35권1호
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• pp.24-31
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• 2012

This study is designed to predict the overall electric power load, to apply the method of time sharing and to reduce simultaneous load factor of electric power when authorized by user entering demand plans and using schedules into the user's interface for a certain period of time. This is about smart grid, which reduces electric power load through simultaneous load factor of electric power reduction system supervision agent. Also, this study has the following characteristics. First, it is the user interface which enables authorized users to enter and send/receive such data as demand plan and using schedule for a certain period of time. Second, it is the database server, which collects, classifies, analyzes, saves and manages demand forecast data for a certain period of time. Third, is the simultaneous load factor of electric power control agent, which controls usage of electric power by getting control signal, which is intended to reduce the simultaneous load factor of electric power by the use of the time sharing control system, form the user interface, which also integrate and compare the data which were gained from the interface and the demand forecast data of the certain period of time.

• 대한산업공학회지
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• 제31권2호
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• pp.106-119
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• 2005

Uncertainties inherent in customer demand patterns make it difficult for supply chains to achieve just-in-time inventory replenishment, resulting in loosing sales opportunity or keeping excessive chain wide inventories. In this paper, we propose two intelligent adaptive inventory control models for a supply chain consisting of one supplier and multiple retailers, with the assumption of information sharing. The inventory control parameters of the supplier and retailers are order placement time to an outside source and reorder points in terms of inventory position, respectively. Unlike most extant inventory control approaches, modeling the uncertainty of customer demand as a stationary statistical distribution is not necessary in these models. Instead, using a reinforcement learning technique, the control parameters are designed to adaptively change as customer demand patterns change. A simulation based experiment was performed to compare the performance of the inventory control models.

• 한국수소및신에너지학회논문집
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• 제17권1호
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• pp.90-97
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• 2006

Hydrogen is used as a chemical feedstock in several important industrial processes, including oil refineries and petro-chemical production. But, nowadays hydrogen is focused as energy carrier on the rising of problems such as exhaustion of fossil fuel and environmental pollution. Thermochemical hydrogen production by nuclear energy has potential to efficiently produce large quantities of hydrogen without producing greenhouse gases, and research of nuclear hydrogen, therefore, has been worked with goal to demonstrate commercial production in 2020. The oil refineries and petro-chemical plant are very large, centralized producers and users of industrial hydrogen, and high-potential early market for hydrogen produced by nuclear energy. Therefore, it is essential to investigate and analyze for state of domestic hydrogen market focused on industrial users. Hydrogen market of petro-chemical industry as demand site was investigated and worked for demand forecast of hydrogen in 2020. Also we suggested possible supply plans of nuclear hydrogen considered regional characteristics and then it can be provided basis for determination of optimal capacity of nuclear hydrogen plant in 2020.

• 산업공학
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• 제24권4호
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• pp.351-361
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• 2011

Forecasting of electricity demand have difficulty in adapting to abrupt weather changes along with a radical shift in major regional and global climates. This has lead to increasing attention to research on the immediate and accurate forecasting model. Technically, this implies that a model requires only a few input variables all of which are easily obtainable, and its predictive performance is comparable with other competing models. To meet the ends, this paper presents an energy demand forecasting model that uses the variable selection or extraction methods of data mining to select only relevant input variables, and employs support vector regression method for accurate prediction. Also, it proposes a novel performance measure for time-series prediction, shift index, followed by description on preprocessing procedure. A comparative evaluation of the proposed method with other representative data mining models such as an auto-regression model, an artificial neural network model, an ordinary support vector regression model was carried out for obtaining the forecast of monthly electricity demand from 2000 to 2008 based on data provided by Korea Energy Economics Institute. Among the models tested, the proposed method was shown promising results than others.

• Industrial Engineering and Management Systems
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• 제8권1호
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• pp.1-13
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• 2009

This paper presents a coordinated planning model of price-dependent demand for a single-manufacturer and a single-retailer. The demand is assumed to be normally distributed, with its mean being price dependent. The manufacturer and retailer coordinate with each other to jointly and simultaneously determine the retail selling price and the retailer order quantity to maximize the joint expected total profit. This model is then compared to a 'returns' policy model where manufacturer buys back unsold items from the retailers. It is shown that the optimal total profit is higher for coordinated planning model than that for the returns policy model, in which the retail price is set by the retailer. A compensation or profit sharing scheme is then suggested and it is shown that the coordinated model with profit sharing yields a 'win-win' situation. Numerical results are presented to illustrate the profit patterns for both linear and nonlinear demand functions. The coordinated planning model, in addition, has a lower optimal price than for a returns policy model, which would result in higher sales, thus expanding the markets for the whole supply chain.

• 한국산학기술학회논문지
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• 제12권11호
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• pp.5178-5187
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• 2011

반도체 산업에 대한 국가직무능력표준에 관련한 개발연구는 부분적으로 수행되었으나 국가직무능력표준을 활용한 산업현장의 훈련수요에 대한 조사와 분석은 이뤄지지 못한 실정이다. 또한 기존의 직업훈련 수요연구는 과부족인원 중심으로 수행되어 직무능력요소에 대한 질적 불일치의 문제가 존재한다. 따라서 본 연구는 반도체 산업을 대상으로 훈련수요 조사를 실시하고 직종별 직무기술요소의 상대적 중요도와 격차를 이용한 시급성 분석을 통해서 해당직종이 갖는 직무능력요소에 대한 정성적 분석결과를 제시하고자 한다. 연구 수행방법으로는 문헌연구와 더불어 반도체 산업에 특화된 직무능력요소의 수요조사를 수행하고, 직종과 직무, 그리고 각 직무능력요소의 정성적 수요를 분석하여 6개의 직종과 28개 직무별 직무능력요소에 대해서 인력수준별로 분석하였다. 또한 기업의 직무기술의 확보 방법과 인력의 충원방법을 분석하고 지역의 대표적 교육과정과 연계를 예시함으로써 직업훈련 프로그램의 적정한 공급 방안을 모색하고자 하였다.

• 한국가스학회지
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• 제24권6호
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• pp.34-46
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• 2020

미래의 안정적인 천연가스 수급을 위해서는 사전에 정확한 수요행태를 파악하고 이를 바탕으로 공급 물량을 확보하는 것이 필요하다. 본 논문은 향후 국내 천연가스 수요 증가의 핵심인 산업용 도시가스의 수요함수 추정 방법론을 제안하여 보다 정확하게 국내 천연가스 수요 특성을 파악하고 안정적인 공급계획 수립에 도움이 되고자 하였다. 국내 304개 산업체의 횡단면 자료를 활용하여 산업용 도시가스 수요함수를 추정하였고, 도시가스 가격, 산업체 매출 이외에 자본투자, 제조원가 등 산업체의 운영 특수성이 수요에 미치는 영향을 도출하였다. 최종적으로 특이치에 강건하고, 오차항의 동분산 및 정규성을 가정하지 않는 최소절대편차추정법을 선택하여 결과 값을 도출하였다. 추가로 산업용 도시가스의 가격탄력성 값을 활용하여 산업용 도시가스의 경제적 가치를 추정하였다. 분석 결과, 산업체에 도시가스를 확대 공급하는 것이 국가 차원에서 이득이 되는 것으로 나타났으며, 따라서 정부는 산업용 도시가스 지원 정책을 통해 보급 확대를 추진할 필요가 있다.