• Journal of the Korean Society of Industry Convergence
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• v.21 no.5
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• pp.207-217
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• 2018

Recently, the importance of energy demand management, particularly peak load control, has been increasing due to the policy changes of the Second Energy Basic Plan. Even though the installation of distributed generation systems such as Photovoltaic and energy storage systems (ESS) are encouraged, high initial installation costs make it difficult to expand their supply. In this study, the power consumption of a university building was measured in real time and the measured power consumption data was used to calculate the optimal installation capacity of the Photovoltaic and ESS, respectively. In order to calculate the optimal capacity, it is necessary to analyze the operation methods of the Photovoltaic and ESS while considering the KEPCO electricity billing system, power consumption patterns of the building, installation costs of the Photovoltaic and ESS, estimated savings on electric charges, and life time. In this study, the power consumption of the university building with a daily power consumption of approximately 200kWh and a peak power of approximately 20kW was measured per minute. An economic analysis conducted using these measured data showed that the optimal capacity was approximately 30kW for Photovoltaic and approximately 7kWh for ESS.

• Industrial Engineering and Management Systems
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• v.14 no.2
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• pp.159-174
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• 2015

Remanufacturing used, end-of-life products is a complex problem involving multiple types of products that may share common parts. Recovery targets assigned by market demand and environmental legislation add more difficulty to the problem. Manufacturers now need to achieve specified take-back and recovery rates while fulfilling demands for remanufactured products. To assists in the demand- and legislation-driven remanufacturing of a family of products (i.e., multiple products that share common parts), this paper introduces a bi-objective mixed integer linear programming (MILP) model for optimizing remanufacturing. The model identifies optimal remanufacturing plans for a product family, whereby, the remanufacturer can achieve demand and recovery targets more profitably and in an environmentally-friendly manner. The model can also be used to quantify and justify the economic and environmental benefits of a product family from a remanufacturing perspective. A case study is presented for remanufacturing an alternatorfamily of products.

• Journal of Forest and Environmental Science
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• v.35 no.3
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• pp.173-180
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• 2019

This study determined the economic impact of environment-friendly cultivation and the optimal cultivation area of Omija (Korean for Schisandra chinensis Baillon) for full-time farmers by analyzing the management performance of existing Omija cultivators. The study divided the target income into urban household income and Omija farm income, and estimate the optimal cultivation area by substituting the target profit from the cost-volume-profit analysis model. The optimum cultivation area was 1.4 ha for general cultivation, 1.08 ha for organic cultivation, and 1.18 ha for pesticide-free farming cultivation considering the average urban household income as the target, and 0.81 ha for general cultivation, 0.63 ha for organic cultivation, and 0.69 ha for pesticide-free farming, considering the average 2012 farm household income as the target. Therefore, the study reached conclusion that it is necessary to secure the price of Omija farm and stable support for income increase. Therefore, the support plan for income stabilization of Omija farm should be considered. Especially, the central government should provide various policies and financial support to help the optimal cultivation area of Omija Farm.

• Journal of the Korean Solar Energy Society
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• v.36 no.5
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• pp.73-89
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• 2016

To assure maximum economic benefits and the energy performance of solar water heating systems, the proper sizing of components and operating conditions need to be optimized. In recent years, a number of studies to design optimally solar water heating systems have been tried. This paper presents a design method for optimizing the various capacity-related and installation-related design variables based on life cycle cost using a genetic algorithm. The design variables considered in this study included the types and numbers of solar collector and auxiliary heaters; the types of storage tanks and heat exchangers; the solar collector slope; mass flow rates of the fluid on the hot and cold sides. The suggested method was applied for optimizing a solar water heating system for an elementary school in Seoul, South Korea. In addition, the effectiveness of the proposed optimization method was assessed by analyzing the obtained optimal solutions of six case studies, each of which was simulated with different solar fractions. It is observed that a trade-off between the equipment cost and the energy cost results in an optimal design that yields the lowest life cycle cost. Therefore, it could be helpful to apply the optimal solar water heating system by comparing the various design solutions obtained by using the optimization method instead of the engineer's experience and intuition.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.4
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• pp.517-526
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• 1999

This paper deals with two economic optimal designs of constant-stress accelerated life test(ALT) where failure distribution follows one of location-scale family, i. e., exponential, Weibull, and lognormal distributions which have been ones of the popular choices of failure distributions. Two optimization criteria to develop ALT plans are the statistical efficiency per unit expected cost which consists of the fixed test cost, cost being proportional to the number of test units, and variable test cost depending on test period and stress level, and the expected loss which combines Taguchi's quadratic loss function and expected test cost. Optimum plan determines the low stress level, test units allocated to each stress, and censoring times at two stress levels under Type I censoring. The proposed ALT plans are illustrated with a numerical example and sensitivity analyses are conducted to study effects of pre-estimates of design parameters.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.9
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• pp.188-196
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• 2003

In order to increase competitiveness and to gain economic benefit, companies ask more and more how to recycle their products in a efficient way. So far, to answer this question, companies are not sufficiently supported by suitable methods specially in the area of disassembly process planning. For this reason, we develop in collaboration with an industrial partner a new method for generating an optimal disassembly sequence. In the presented paper this method will be described in detail by considering the exiting assembly information, disassembly method and disassembly depth. PLM (Profit-Loss Margin) curve that is used to determine disassembly depth consists of profit value, disassembly cost and disassembly effect. Using assessment parameters, generated alternative disassembly sequences are evaluated and optimal disassembly sequence is proposed. This method is applied to generate the optimal disassembly sequence of Door Trim as an example.

• KIEAE Journal
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• v.11 no.6
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• pp.81-86
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• 2011

By strengthening the insulation performance of a building, a great deal of energy can be saved and a comfortable indoor environment can be offered to people. On the other hand, the climate, which has a great influence on the indoor environment, is changed by global warming. Therefore, in planning building envelope structure and design, climate change should be considered. In this paper, the optimal insulation thickness of exterior walls was calculated by an economic assessment method using heating degree-days. Additionally, how much influence climate change has on planning building insulation was investigated. The examination showed that heating degree-days have decreased by about 10% due to climate change in the past few decades. It was also shown that the optimal insulation thickness of exterior walls was thin, at about 6%, in three representative Korean cities (Seoul, Daejeon, Jeju).

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.10a
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• pp.100-105
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• 2003

With the recent development of machining technology, high speed machining process is widely used for-the mold and difficult-to -cut-materials machining since it allows achieving high productivity and surface quality. However, during the high speed machining process, high cutting speed and feed rate can cause abrupt tool life decrease due to rapid rising of the cutting tool temperature. Such situation may cause increase of machining cost. Thus, in this study, developed optimization algorithm is applied to determine optimal machining variables for multiple high speed machining. The R-T characteristic curve for machining economics problems with a linear-lorarithmic tool life model is determined by applying sensitivity analysis. finally, a series of high speed machining experiments are performed to determine the desired optimal machining variables, and the results are analyzed.

• Hwankyungkyoyuk
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• v.13 no.2
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• pp.38-50
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• 2000

We are evidently Home Economicus, egoistic rational utility maximiger, and all the capitalism economic situation make us adapt to such life, and recognize that it is rational to act like that. This can be demonstrated in Prisoner′s Dilemma(PD) which always select the non-cooperative choice for free rider in rational selection process of public goods. This paper notice the "what is problem\ulcorner"The problem is not in free rider itself but in free rider egoism. The practical behavior of free rider egoism can be explained by way of Prisoner′s Dilemma. In PD situation, the prisoner makes a rational choice, non-cooperative alternative, but he doesn′arrive at preto-optimality. It is dilemma. Why can′t he arrive \ulcorner Because he is isolated from other prisoner. So we call it prisoner′s dilemma. The PD situation can be compared with our real economic life, which, we think, have kept by rational choice of the public goods. We actually have made our life as an individual one although we organized communities of capitalism. Of course, we know each others as members of same society, but each individual being can′t secure the belief, which has composed basis of community. So, it is very similar and common between PD situation and our real economic life in the production of public goods. We conclude that this non-cooperative process of PD situation can be utilized as instrument of EE. So this non-cooperative process can show us the effectiveness of EE as follows. \circled1 Game situation life PD can be used as good instrument for explaining the rational selection dilemma(error) to Homo-Economicus, the rational agent, with the optimal and rational language. \circled2 We can show that the selection result is dilemma, not arrive pareto - optimality. \circled3 The dilemma can be resolved with accomplishing the good communal life based on the belief, not on the isolation.

• Journal of Korean Society for Quality Management
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• v.49 no.3
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• pp.341-358
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• 2021

Purpose: After product development, a Reliability Demonstration Test(RDT) is performed to confirm that the target life has been achieved. In the RDT, there are cases where the test equipment cannot accommodate all samples. Therefore, this study considers a test method to most economically demonstrate the target life of the product at a certain confidence level when the sample size is larger than the capacity of the test equipment. Methods: If the sample size is larger than the capacity of the test equipment, test equipments may be added or the test time of individual samples may be increased. So the test method is designed to cover this situation with limited capacity. A zero-failure test method is applied as a test method to RDT. To minimize the cost, the test cost is defined and the cost function is obtained. Finally, we obtain the optimal test plan. Results: A zero-failure test method is designed when the sample size is larger than the capacity of the test equipment, and the expected total cost is derived. In addition, the process of calculating the appropriate sample size, test time, and number of test equipment is illustrated through an example, and the effects of model parameters to the optimal solutions are investigated numerically. Conclusion: In this paper, we study a zero-failure RDT with test equipment that has limited capacity. The expected total cost is derived and the optimal sample size, test time, and number of test equipment are determined to minimize the expected total cost. We also studied numerical examples and for further studies, we can relax some restrictions in the test model and optimize the test method.