• 한국기계가공학회지
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• 제14권1호
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• pp.44-50
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• 2015

This paper presents a heuristic process-optimization procedure for minimizing warpage in injection-molded parts based on the dynamic robust design methodology. The injection molding process is known to have intrinsic variations of its process conditions due to various factors, including incomplete process control facilities. The aim of the robust design methodology advocated by Taguchi is to determine the optimum design variables in a system which is robust to variations in uncontrollable factors. The proposed procedure can determine the optimal robust conditions of injection molding processes at a minimum cost through a trade-off strategy between the degree of warpage and the packing time.

• Journal of Electrical Engineering and Technology
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• 제8권6호
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• pp.1261-1268
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• 2013

This study proposes a voltage and reactive coordinative control strategy with distributed generator (DG) in a distribution power system. The aim is to determine the optimum dispatch schedules for an on-load tap changer (OLTC), distributed generator settings and all shunt capacitor switching on the load and DG generation profile in a day. The proposed method minimizes the real power losses and improves the voltage profile using squared deviations of bus voltages. The results indicate that the proposed method reduces the real losses and voltage fluctuations and improve receiving power factor. This paper proposes coordinated voltage and reactive power control methods that adjust optimal control values of capacitor banks, OLTC, and the AVR of DGs by using a voltage sensitivity factor (VSF) and dynamic programming (DP) with branch-and-bound (B&B) method. To avoid the computational burden, we try to limit the possible states to 24 stages by using a flexible searching space at each stage. Finally, we will show the effectiveness of the proposed method by using operational cost of real power losses and voltage deviation factor as evaluation index for a whole day in a power system with distributed generators.

• Journal of Power Electronics
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• 제18권3호
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• pp.789-801
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• 2018

Model predictive direct power control (MPDPC) is a widely recognized high-performance control strategy for a three-phase grid-connected pulse width modulation (PWM) rectifier. Unlike those of conventional grid-connected PWM rectifiers, the active and reactive powers of permanent magnet synchronous generator (PMSG)-connected PWM rectifiers, which are used in electromagnetic transmitters, cannot be calculated as the product of voltage and current because the back electromotive force (EMF) of the generator cannot be measured directly. In this study, the predictive power model of the rectifier is obtained by analyzing the relationship among flux, back EMF, active/reactive power, converter voltage, and stator current of the generator. The concept of duty cycle control in the proposed MPDPC is introduced by allocating a fraction of the control period for a nonzero vector and rest time for a zero vector. When nonzero vectors and their duration in the predefined cost function are simultaneously evaluated, the global power ripple minimization is obtained. Simulation and experimental results prove that the proposed MPDPC strategy with duty cycle control for the PMSG-connected PWM rectifier can achieve better control performance than the conventional MPDPC-SVM with grid-connected PWM rectifier.

• 한국가스학회지
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• 제20권1호
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• pp.7-12
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• 2016

천연가스는 장거리 수송을 위해서는 액화가 필수적으로 이루어진다. 액화공정 내 압축기에서 특히 많은 동력이 요구되며, 동력을 공급하기 위해서는 동력기가 필요하다. 여러 가지 동력기 중 어떠한 동력기를 선택하느냐에 따라 동력 공급에 필요한 비용이 변하게 된다. 본 연구에서는 최소의 비용으로 천연가스 액화공정에 동력을 공급하는 최적의 동력기 선택을 위해 최적화를 수행하였다. 또한 가스전의 용량을 고려하여 일정한 가스전에서 천연가스가 추출부터 소멸될 때까지의 전체기간 동안에 추출되는 속도가 변경되는 시나리오를 구성하였다. 공정모사를 통해 동력기 장치의 비용과 운전비용 간의 상관관계를 예측하였으며, 장치의 수명 등을 고려하여 모델링하였다. 그 결과 최대 6.4%의 비용을 감소하는 최적의 동력기 모델을 설계하였다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2007년도 한국지능정보시스템학회
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• pp.101-110
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• 2007

본 연구는 웹의 플랫폼화에 대응하기 위한 서비스 유통 및 소프트웨어 개발방식의 핵심이슈로 '규모의 경제'와 '서비스화'이라는 모순적인 요구를 동시적으로 해결하는 것임을 제시했다. 소프트웨어 관점에서 본 이른바 웹 2.0 시대의 주요한 특징은 웹의 플랫폼화와 롱테일 서비스 시장의 등장이다. 웹이 독립적인 유통채널로 기능하게 되는데, 본 연구는 개발자 및 사용자 커뮤니티를 구축하기 위한 플랫폼전략을 규모의 경제와 상호소통(Interaction)의 관점에서 분석했다. 플랫폼 전략에서 제기된 이슈를 해결하기 위해서는 소프트웨어 개발전략도 오픈소스 커뮤니티를 활용한 레고형 개발이 필요하다. 비용절감과 사용자 채널을 확보하기 위해서는 오픈소스 커뮤니티를 이용한 조직화방식이 필요하고, 고객화된 서 비스의 가격경쟁 력을 확보 하기 위한 레고형 개발 방법이 필요하다.

• Industrial Engineering and Management Systems
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• 제12권3호
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• pp.207-223
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• 2013

Revenue management (RM) has been widely used to model products characterized as perishable. Classical RM model assumed that price is the sole factor in the model. Thus price adjustment becomes a crucial and costly factor in business. In this paper, an optimal pricing model is developed based on minimization of soft customer cost, one kind of price adjustment cost and is solved by Lagrange multiplier method. It is formed by expected discounted revenue/bid price integrating quantity-based RM and pricing-based RM. Quantity-based RM consists of two capacity models, namely, booking limit and overbooking. Booking limit, built by assuming uncertain customer arrival, decides the optimal capacity allocation for two market segments. Overbooking determines the level of accepted order exceeding capacity to anticipate probability of cancellation. Furthermore, pricing-based RM models occupancy/demand rate influenced by internal and competitor price changes. In this paper, a mathematical model based on game theoretic approach is developed for two conditions of deterministic and stochastic demand. Based on the equilibrium point, the best strategy for both hotels can be determined.

• 한국방사성폐기물학회:학술대회논문집
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• 한국방사성폐기물학회 2005년도 Proceedings of The 6th korea-china joint workshop on nuclear waste management
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• pp.290-299
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• 2005

Two decommissioning projects are carried out at the KAERI (Korean Atomic Energy Research Institute), one for the Korea research reactors, KRR-1 and KRR-2, and another for the uranium conversion plant (UCP). The concept of the management of the wastes from the decommissioning sites was reviewed with a relation of the decommissioning strategies, technologies for the treatment and the decontamination, and the characteristics of waste. All the liquid waste generated from KRR-1 and KRR-2 decommissioning site is evaporated by a solar evaporation facility and all the liquid waste from the UCP is treated together with lagoon sludge waste. The solid wastes from the decommissioning sites are categorized into three groups; not contaminated, restricted releasable and radioactive waste. The not-contaminated waste will be reused and/or disposed at an industrial disposal site, and the releasable waste is stored for the future disposal at the KAERI. The radioactive waste is packed in containers, and will be stored at the decommissioning sites till they are sent to a national repository site. The reduction of the radioactive solid waste is one of the strategies for the decommissioning projects and could be achieved by the repeated decontamination. By the achievement of the minimization strategy, the amount of radioactive waste was reduced and the disposal cost will be reduced, but the cost for manpower, for direct materials and for administration was increased.

• Journal of Information Processing Systems
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• 제17권4호
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• pp.721-736
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• 2021

For the mobile edge computing (MEC) system supporting dense network, a joint allocation algorithm of computing and communication resources based on reinforcement learning is proposed. The energy consumption of task execution is defined as the maximum energy consumption of each user's task execution in the system. Considering the constraints of task unloading, power allocation, transmission rate and calculation resource allocation, the problem of joint task unloading and resource allocation is modeled as a problem of maximum task execution energy consumption minimization. As a mixed integer nonlinear programming problem, it is difficult to be directly solve by traditional optimization methods. This paper uses reinforcement learning algorithm to solve this problem. Then, the Markov decision-making process and the theoretical basis of reinforcement learning are introduced to provide a theoretical basis for the algorithm simulation experiment. Based on the algorithm of reinforcement learning and joint allocation of communication resources, the joint optimization of data task unloading and power control strategy is carried out for each terminal device, and the local computing model and task unloading model are built. The simulation results show that the total task computation cost of the proposed algorithm is 5%-10% less than that of the two comparison algorithms under the same task input. At the same time, the total task computation cost of the proposed algorithm is more than 5% less than that of the two new comparison algorithms.

• Nuclear Engineering and Technology
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• 제55권5호
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• pp.1838-1854
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• 2023

This paper presents a hybrid algorithm to solve the multi-objective path planning (MOPP) problem for mobile robots in a static nuclear accident environment. The proposed algorithm mimics a real nuclear accident site by modeling the environment with a two-layer cost grid map based on geometric modeling and Monte Carlo calculations. The proposed algorithm consists of two steps. The first step optimizes a path by the hybridization of improved ant colony optimization algorithm-modified A^* (IACO-A^*) that minimizes path length, cumulative radiation dose and energy consumption. The second module is the high radiation dose rate avoidance strategy integrated with the IACO-A^* algorithm, which will work when the mobile robots sense the lethal radiation dose rate, avoiding radioactive sources with high dose levels. Simulations have been performed under environments of different complexity to evaluate the efficiency of the proposed algorithm, and the results show that IACO-A^* has better path quality than ACO and IACO. In addition, a study comparing the proposed IACO-A^* algorithm and recent path planning (PP) methods in three scenarios has been performed. The simulation results show that the proposed IACO-A^* IACO-A^* algorithm is obviously superior in terms of stability and minimization the total cost of MOPP.

• Journal of Information Technology Applications and Management
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• 제14권3호
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• pp.95-113
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• 2007

To minimize IT operational risks and the opportunity cost for lost business hours. it is necessary to have preparedness in advance and mitigation activities for minimization of a loss due to the business discontinuity. There are few cases that banks have a policy on systematic management, system recovery and protection activities against system failure. and most developers and system administrators response based on their experience and the instinct. This article focuses on the mitigation model development for minimizing the incidents of disk unit in IT operational risks. The model will be represented by a network model which is composed of the three items as following: (1) the risk factors(causes, attributes and indicators) of IT operational risk. (2) a periodic time interval through an analysis of historical data. (3) an index or an operational regulations related to the examination of causes of an operational risk. This article will be helpful when enterprise needs to hierarchically analyze risk factors from various fields of IT(information security, information telecommunication, web application servers and so on) and develop a mitigation model. and it will also contribute to the reduction of operational risks on information systems.