• Progress in Superconductivity and Cryogenics
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• v.1 no.1
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• pp.48-55
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• 1999

thermodynamic cycle analysis has been performed for the power generation systems to utilize the cold energy of liquefied natural gas (LNG). The power cycle used the air or water at room temperature as a heat source and the LNG at cryogenic temperature as a heat sink. Among manypossible configurations of the cycle. the open Rankine cycle. and the closed Brayton cycle, and the closed Rankine cycle are selected for the basic analysis because of their practical importance. The power output per unit mass of LNG has been analytically calculated for various design parameters such as the pressure ratio. the mass flow rate. the adiabatic efficiency. the heat exchanger effectiveness. or the working fluid. The optimal conditions for the parameters are presented to maximize the power output and the design considerations are discussed. It is concluded that the open Rankine cycle is the most recormmendable both in thermodynamic efficency and in practice.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.704-711
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• 2005

Recently Life Cycle Cost Analysis for civil infrastructures such as pavements, bridges, and dams has been emphasized However, so far, there are few systems available for life cycle cost analysis of bridges at design stage. Therefore, the objective of this paper is to develop a user-friendly life-cycle cost analysis system for LCC-effective optimal design decision making at design stage. The program is based on the proposed LCC model, formulation, analysis modules and systematic procedure that suit Korean construction conditions. It is expected that the developed system can be effectively utilized for more LCC-effective design of bridges. It is applied to an actual bridge design project in order to demonstrate its effectiveness and applicability.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.1
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• pp.225-229
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• 1990

As a basic study of optimal design conditions of refrigeration systems, the reversed carnot cycle, including heat transfer processes through the finite temperature differences between heat sources and the working fluids, is analyzed with the capacity of heat exchanger as a design parameter. When the temperatures of heat sources and the input work are fixed as constants, the optimal design condition is obtained as an optimum ratio of capacities of heat exchangers, which is exactly unity when the exergy output and effectiveness are maximum. In addition, the optimum ratio is slightly increased from unity as the irreversibility of the cycle increases.

• Archives of design research
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• v.18 no.3 s.61
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• pp.139-148
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• 2005

Generally, the brand has its life cycle as the product has. This life cycle is classified into the stages; introduction, growth, maturity and decline. Since the brand is little different from that of the product's, we can find some differences when it applies to the brand. The most effective method to perceive the brand to the consumers is advertisement, therefore in the advertisement design, it is important to figure out the current stage in the brand life cycle and use the most ideal design strategy in that stage. This study suggests the concept of the brand life cycle and the most effective strategy in each stages of the advertisement design. In the stage of the brand introduction, we apply the 'What is it? Strategy' which introduces the brand itself. In the stage of the growth, 'How does it Differ from? Strategy' is suggested as the advertisement strategy emphasizing the positioning which shows its differential competitive advantages among brands because in this stage there are many competitive brands in the market. In the stage of the maturity, we focus on the 'What does it Convey of? Strategy' stressing on the delivery of brand's value to consumers as consumers they purchase the brand. Finally in the stage of the decline, 'What does it Stand for? Strategy' is suggested in order to emphasize the generation of brand's symbolical meaning rather than to emphasize it's attributes or benefits. Therefore the advertisement design needs the contingent ideal design strategy according to the stages of brand life cycle and the effective brand management through it.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.115-120
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• 1997

Environmental Product Life Cycle Management is an activity for defining and describing the product, process or activity environmentally. Especially, the main responsibility for the environmental impact of products lies in the design phase of product. Designers cany a heavy responsibility to determine technical, economic and ecological properties of the product. So in order to help designers, structured understanding and application of treating large amount of data and infonnation should be considered. This paper presents a methodological approach for decision supporting to build Product Life Cycle Management system and show a set of database modeling. Additionally, a key issue for databases is the quality of the provided information.

• Proceedings of the KAIS Fall Conference
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• 2004.06a
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• pp.335-338
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• 2004

Life-Cycle Engineering(LCE) is a decision-making methodology that considers environmental and cost needs during the product life-cycle. Environmental conscious design and manufacturing has become more and more important and it has been enforced by governmental regulations and used as trade restriction. LCE involves integrating environmental consideration into new product development including design, material selection, manufacturing processes and distribution of the product to the consumers, plus the end-of-life management such as disassembly, material recovery, remanufacturing of the product after discarding it. In this paper, a state-of-the-art survey of LCE is presented.

• Journal of the Korea Safety Management & Science
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• v.7 no.5
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• pp.155-174
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• 2005

Parametric life-cycle cost(LCC) models have been integrated with traditional design tools, and used in prior work to demonstrate the rapid solution of holistic, analytical tradeoffs between detailed design variations. During early designs stages there may be competing concepts with dramatic differences. Additionally, detailed information is scarce, and decisions must be models. for a diverse range of concepts, and the lack of detailed information make the integration make the integration of traditional LCC models impractical. This paper explores an approximate method for providing preliminary life-cycle cost. Learning algorithms trained using the known characteristics of existing products be approximated quickly during conceptual design without the overhead of defining new models. Artificial neural networks are trained to generalize on product attributes and life cycle cost date from pre-existing LCC studies. The Product attribute data to quickly obtain and LCC for a new and then an application is provided. In additions, the statistical method, called regression analysis, is suggested to predict the LCC. Tests have shown it is possible to predict the life cycle cost, and the comparison results between a learning LCC model and a regression analysis is also shown

• Korean Journal of Construction Engineering and Management
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• v.15 no.3
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• pp.113-119
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• 2014

Recently, the demand on the practical application of life-cycle cost effectiveness for design and rehabilitation of structure is rapidly growing unprecedently in engineering practice. Accordingly, in the 21st century, it is almost obvious that life-cycle cost together with value engineering will become a new paradigm for all engineering decision problems in practice. However, in spite of impressive progress in the researches on the LCC, the most researches have only focused on the Deterministic or Probabilistic LCC analysis approach (Level-1 LCC Model) at design stage. Thus, the goal of this study is to develop a practical and realistic methodology for the Lifetime risk based Life-Cycle Cost (LCC)-effective optimum decision-making at design stage.

• Transactions of Materials Processing
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• v.14 no.4 s.76
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• pp.368-374
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• 2005

In the present study we used a diagrammatic analysis of 6 sigma quality control and Taguchi method for injection molding of monitor back-cover, evaluated the influence on the cycle time with part design, mold design, molding process and standardization activity involving design and molding, adopted analysis of sensitivity and effective factors of the part design and molding process conditions for productivity, identified main design molding factors. The contributing factors for the final cycle time could be enumerated as follows; the thickness of hot spot, main nominal part thickness, coolant inlet temperature, melt temperature and cooling line layout, etc.. As a first step, all the critical factors of design process applied to the current monitor housing were investigated through 6 sigma process. Thereafter, the optimal and better critical factors found in the first step were applied to new product design to prove that our process was correct. The Moldflow was used for injection molding simulation, and Minitab software for the statistical analysis, respectively. Finally, the productivity of new design was increased about 33 percents for our specific case.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.221-229
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• 2003

In the early phases of the product life cycle, Life Cycle Assessment (LCA) is recently used to support the decision-making fer the conceptual product design and the best alternative can be selected based on its estimated LCA and its benefits. Both the lack of detailed information and time for a full LCA fur a various range of design concepts need the new approach fer the environmental analysis. This paper suggests a novel approximate LCA methodology for the conceptual design stage by grouping products according to their environmental characteristics and by mapping product attributes into impact driver index. The relationship is statistically verified by exploring the correlation between total impact indicator and energy impact category. Then a neural network approach is developed to predict an approximate LCA of grouping products in conceptual design. Trained learning algorithms for the known characteristics of existing products will quickly give the result of LCA for new design products. The training is generalized by using product attributes for an ID in a group as well as another product attributes for another IDs in other groups. The neural network model with back propagation algorithm is used and the results are compared with those of multiple regression analysis. The proposed approach does not replace the full LCA but it would give some useful guidelines fer the design of environmentally conscious products in conceptual design phase.