• IE interfaces
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• v.22 no.4
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• pp.368-375
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• 2009

This paper considers a two-stage supply system consisting of two make-to-stock facilities. The facility in the first stage produces a single type of component in anticipation of future demands from the market and the end item production while the facility in the second stage produces the end item in anticipation of future demands from the OEM customers. The facility in the first stage has the option of to accept or reject each incoming demand from the market. In this paper, we address the problem of how to control the exogenous component demand and how to manage the production of the end item and the component so as to maximize the system's profit subject to the system costs. In this paper, we present a heuristic policy that is the base-stock production policy combined with a linear switching curve for component demand control. Numerical study is implemented under different operating conditions of the system and it shows that the performance of the heuristic is very promising compared to that of the optimal policy for the Markov model.

• Journal of Preventive Medicine and Public Health
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• v.16 no.1
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• pp.113-120
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• 1983

The main objective of this case study is to develop demand forecasting model for durg inventory control in a university hospital. This study is based on the pertinent records during the period of January 1975 to August 1981 in the pharmacy and stock departments of the hospital. Through the analysis of the above records the author made some major findings as follows: 1. In A.B.C. classification, the biggest demand (A class) consists of 9 items which include 6 items of antibiotics. 2. Demand forecasting level of an index or discrepancy in A class drug compared with real demand for 6 months is average 30.4% by X-11 Arima method and 84.6% by Winter's method respectively. 3. After the correcting ty the number of bed, demand forecasting of drug compared with real demand for 6 months is average 23.1% by X-11 Arima method and 46.6% by Winter's method respectively.

• Proceedings of the KIEE Conference
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• 2001.05a
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• pp.197-200
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• 2001

In this paper, a novel demand control technique using composite fuzzy model is developed for the peak load control. The outcome of the study clearly indicates that the composite model approach can be used as an attractive and effective means of the peak demand control.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.169-171
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• 1999

This paper presents a new demand control technique using fuzzy logic. Generally, predictive demand control method often brings about a large number of control actions and undesirable alarm during the beginning stage of the demand period. To solve this problem, a fuzzy predictive algorithm is proposed. The main idea of the method is the determination of sensitivity factor by using fuzzy logic. The performance of the proposed algorithm is tested through a case study.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.235-240
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• 2006

The existing inventory managements bear a relation to forecasting or assumptions. So these methods become more complicated and more expensive systems as time goes. This paper developed a practical inventory system which is called DCC(demand control chart). DCC does not 'forecast' but 'control' the trend of demand without assumptions. According to the trend of sales, DCC adjusts an order quantity considering the capacity of shelf in a store. Specially, DCC is a useful method under FRID system. Besides, this paper introduces EPFR(Every Period Full Replenishment) policy for reducing stocks.

• Journal of Satellite, Information and Communications
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• v.11 no.2
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• pp.36-41
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• 2016

In order to take advantage of the building as an energy demand resources, it requires automated systems that can respond to the demand response event. Load aggregator has been started business in Korea, research and development of building energy management and demand response systems that can support them has been active recently. However, the ratio of introducing automated real-time demand response systems is insufficient and the cost is also high. In this research, we developed a building energy management system and OpenADR protocol to participate in a demand response and then evaluated them in real building. OpenADR is a standard protocol for automated system through the event and reporting between load aggregator and demand-side. In addition, we also developed a web-based building control system to embrace different control systems and to reduce the peak load during demand response event. We verified that the result systems are working in a building and the reduced load is measured to confirm the demand response.

• Journal of Korean Institute of Industrial Engineers
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• v.31 no.2
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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.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.15 no.3
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• pp.203-209
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• 2003

Control algorithms of an air handling unit by using the mixing box plenum pressures were developed and verified by experiments. Control algorithms developed for this study were the setpoint algorithms for the outdoor damper position, the outdoor/fixed plenum pressure, and the return/exhaust plenum pressure. The outdoor/fixed plenum pressure setpoint was used to control the bypass damper position, and the return/exhaust plenum pressure setpoint was used to control the return fan speed. Experimental results showed the good control of the required outdoor air demand. Therefore, setpoint algorithms developed for this study may effectively be applied for the control of the VAV air handling unit.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.3
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• pp.137-143
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• 2014

Demand Controller is a load control device that monitor the current power consumption and calculate the forecast power to not exceed the power set by consumer. Accurate demand forecasting is important because of controlling the load use the way that sound a warning and then blocking the load when if forecasted demand exceed the power set by consumer. When if consumer with fluctuating power consumption use the existing forecasting method, management of demand control has the disadvantage of not stable. In this paper, load forecasting of the unit of seconds using the Exponential Smoothing Methods, ARIMA model, Kalman Filter is proposed. Also simulation of load forecasting of the unit of the seconds methods and existing forecasting methods is performed and analyzed the accuracy. As a result of simulation, the accuracy of load forecasting methods in seconds is higher.

• The Journal of Fisheries Business Administration
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• v.47 no.4
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• pp.65-75
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• 2016

The purpose of this study was to analyze the production and marketing control effects of aqua-cultured flounder required for stable income growth of aqua-cultured household. We analyzed the supply and demand structure of cultured flounder using the partial equilibrium model approach. And we estimated the optimal yield of cultured flounder and analyzed the effect of marketing control through constructed model. The main results of this study are summarized as follows. First, the fitness and predictive power of the estimated model showed that the RMSPE and MAPE values were less than 5% and Theil's inequality coefficient was very close to 0 rather than 1. It was evaluated that the prediction ability of the aqua-cultured flounder supply and demand model by dynamic simulation was excellent. Second, dynamic simulation based on policy simulation was conducted to analyze the price increase effect of production and shipment control of cultured flounder. As a result, if the annual production volume is reduced by 1%, 5%, and 10% among 32,852~37,520 tons, it is analyzed that the price increase effect is from 1.2% to 12.5%. Finally, this study suggests that the production and marketing control can increase the price of aqua-cultured flounder in the market. In this paper, we propose a policy implementation of the total supply system instead of conclusions.