• 제어로봇시스템학회논문지
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• 제6권2호
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• pp.207-216
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• 2000

This paper introduces an effective system design method to develop a customer oriented product using a design optimization process and to select a set of critical design paramenters,. The process results in the development of a successful product satisfying customer needs and reducing development risk. The proposed scheme adopted a five step QFD(Quality Function Deployment) in order to extract design parameters from customer needs and evaluated their priority using risk factors for extracted design parameters. In this process we determine critical design parameters and allocate them to subsystem designers. Subsequently design engineers develop and test the product based on these parameters. These design parameters capture the characteristics of customer needs in terms of performance cost and schedule in the process of QFD, The subsequent risk management task ensures the minimum risk approach in the presence of design parameter uncertainty. An application of this approach was demonstrated in the development of weld quality monitoring system. Dominant design parameters affect linearity characteristics of weld defect feature vectors. Therefore it simplifies the algorithm for adopting pattern classification of feature vectors and improves the accuracy of recognition rate of weld defect and the real time response of the defect detection in the performance. Additionally the development cost decreases by using DSP board for low speed because of reducing CPU's load adopting algorithm in classifying weld defects. It also reduces the cost by using the single sensor to measure weld defects. Furthermore the synergy effect derived from the critical design parameters improves the detection rate of weld defects by 15% when compared with the implementation using the non-critical design parameters. It also result in 30% saving in development cost./ The overall results are close to 95% customer level showing the effectiveness of the proposed development approach.

• 대한조선학회논문집
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• 제31권3호
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• pp.154-164
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• 1994

본 연구에서는 경제적이고, 품질이 우수한 용접 조립보의 생산을 위해 요구되는 조건을 컴퓨터 시뮬레이션 방법 및 최적화 방법을 이용해서 찾고자 한다. 이를 위해 용접 조건과 가열 조건 등 조립보의 생산 과정을 지배하는 변수를 선정하고, 이 변수에 따라 조립보 생산비를 추정할 수 있는 모델을 제시하여, 생산에 따른 제한 조건을 만족시키면서, 생산비가 최소가 되는 생산 변수를 구하였다. 더 나아가서 설계 및 생산의 통합 제어를 위해 용접 조립보의 생산에 따른 총 비용을 산출할 수 있는 추정식을 제시하고, 선급 규정에 따라 설계하는 과정까지 포함하여 최적화를 수행하였다. 또한 곡직가열이 불가능한 경우를 가정하여, 가중치법에 기초한 다목적 최적화 기법을 도입하고 최소 비용과 최소 변형의 절충해를 얻는 방법을 제시하였다.

• 대한조선학회논문집
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• 제50권1호
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• pp.59-68
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• 2013

Nowadays, optimum structural design techniques based on CSR have been developed and applied to the preliminary design stage focused on minimum weight and minimum construction cost of ship structure. Optimum structural design algorithm developed before could minimize weight and cost on fixed compartment arrangement. However, to develop more efficient design technique, a designer needs to combine optimized compartment arrangement with optimized ship structural design because compartment arrangement has a large effect on structural design according to the change of still water bending moment as a consequence of compartment arrangement change. In this study, automated algorithm for compartment arrangement of an oil tanker is developed to apply preliminary structural design. The usefulness of developed algorithm is verified with Aframax oil tanker constructed by STX shipbuilding Co.Ltd..

• 한국강구조학회 논문집
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• 제19권1호
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• pp.15-27
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• 2007

지난 10년간 건설 환경에서 노무비는 재료비에 대해 상대적으로 계속해서 증가하고 있다. 따라서 강구조물의 최적 설계를 위해 널리 쓰이고 있는 최소중량설계는 더 이상 최소경비설계를 의미하지 못한다. 최근의 강 구조물의 제작 시 재료비 외에 부재연결에 소요되는 경비가 실제로 총 제작비에 커다란 영향을 미치는 것을 알 수 있다. 그럼에도 불구하고 대부분의 연구가 최소 중량설계나 구조물의 고등해석에만 이루어지고 있다. 따라서 본 연구는 횡 방향 하중에 효과적으로 저항하도록 보와 기둥이 모멘트 연결된 강 뼈대 구조물을 대상으로 안정성에 문제가 없이 경비절감에 효과적인 설계를 위해 재료비뿐만 아니라 제작비 및 현장에서 가설 시 부재연결에 소요되는 경비를 포함하는 최소 경비 설계를 수행하고자 한다. 하중저항계수설계법에 따른 전단과 처짐 및 보-기둥 상관관계식을 포함하는 비선형 해석과정과 유전알고리즘을 바탕으로 한 최적화 알고리즘을 결합하여 모멘트 부재연결의 수를 줄이고 또한 효과적인 배치를 수행함으로 최적 설계 해 및 모멘트 연결의 수와 총 경비와의 상반관계를 나타내고 이로부터 최적의 모멘트 연결의 수 및 그 배치를 구하였다. 현실적인 하중조건을 고려한 수치 예를 통해 본 연구의 적용성과 효율성을 나타내었다.

• Smart Structures and Systems
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• 제16권1호
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• pp.1-26
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• 2015

Minimizing construction cost and reducing seismic damage are two conflicting objectives in the design of any new structure. In the present work, we try to develop a framework in order to solve the optimum performance-based design problem considering the construction cost and the seismic damage of steel moment-frame structures. The Park-Ang damage index is selected as the seismic damage measure because it is one of the most realistic measures of structural damage. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. To improve the time efficiency of the proposed framework, three simplifying strategies are adopted: first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication; second, fitness approximation decreasing the number of fitness function evaluations; third, wavelet decomposition of earthquake record decreasing the number of acceleration points involved in time-history loading. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency's (FEMA) recommended seismic design specifications. The results from numerical application of the proposed framework demonstrate the efficiency of the framework in solving the present multi-objective optimization problem.

• Nuclear Engineering and Technology
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• 제50권1호
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• pp.126-131
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• 2018

As it is known, uranium enrichment is carried out on industrial scale by means of multistage separation facilities, i.e., separation cascades in which gas centrifuges (GCs) are connected in series and parallel. Design and construction of these facilities require significant investment. So, the problem of calculation and optimization of cascade working parameters is still relevant today. At the same time, in many cases, the minimum unit cost of a product is related to the cascade having the smallest possible number of separation elements/GCs. Also, in theoretical studies, it is often acceptable to apply as an efficiency criterion the minimum total flow to supply cascade stages instead of the abovementioned minimum unit cost or the number of separation elements. In this article, cascades with working parameter of a single GC changing from stage to stage are optimized by two of the abovementioned performance criteria and are compared. The results obtained allow us to make a conclusion about their differences.

• International Journal of Aeronautical and Space Sciences
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• 제17권2호
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• pp.268-283
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• 2016

Aircraft manufacturing companies have to consider multiple derivatives to satisfy various market requirements. They modify or extend an existing aircraft to meet new market demands while keeping the development time and cost to a minimum. Many researchers have studied the derivative design process, but these research efforts consider baseline and derivative designs together, while using the whole set of design variables. Therefore, an efficient process that can reduce cost and time for aircraft derivative design is needed. In this research, a more efficient design process is proposed which obtains global changes from local changes in aircraft design in order to develop aircraft derivatives efficiently. Sensitivity analysis was introduced to remove unnecessary design variables that have a low impact on the objective function. This prevented wasting computational effort and time on low priority variables for design requirements and objectives. Additionally, uncertainty from the fidelity of analysis tools was considered in design optimization to increase the probability of optimization results. The Reliability Based Design Optimization (RBDO) and Possibility Based Design Optimization (PBDO) methods were proposed to handle the uncertainty in aircraft conceptual design optimization. In this paper, Collaborative Optimization (CO) based framework with RBDO and PBDO was implemented to consider uncertainty. The proposed method was applied for civil jet aircraft derivative design that increases cruise range and the number of passengers. The proposed process provided deterministic design optimization, RBDO, and PBDO results for given requirements.

• Computers and Concrete
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• 제6권3호
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• pp.253-268
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• 2009

This study aims to develop a cost-based high-performance concrete (HPC) mix optimization system based on an integrated approach using artificial neural networks (ANNs) and genetic algorithms (GA). ANNs are used to predict the three main properties of HPC, namely workability, strength and durability, which are used to evaluate fitness and constraint violations in the GA process. Multilayer back-propagation neural networks are trained using the results obtained from experiments and previous research. The correlation between concrete components and its properties is established. GA is employed to arrive at an optimal mix proportion of HPC by minimizing its total cost. A system prototype, called High Performance Concrete Mix-Design System using Genetic Algorithm and Neural Networks (HPCGANN), was developed in MATLAB. The architecture of the proposed system consists of three main parts: 1) User interface; 2) ANNs prediction models software; and 3) GA engine software. The validation of the proposed system is carried out by comparing the results obtained from the system with the trial batches. The results indicate that the proposed system can be used to enable the design of HPC mix which corresponds to its required performance. Furthermore, the proposed system takes into account the influence of the fluctuating unit price of materials in order to achieve the lowest cost of concrete, which cannot be easily obtained by traditional methods or trial-and-error techniques.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 추계학술대회 논문집
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• pp.1158-1164
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• 2007

Recently, the demand on the practical application of life-cycle cost effectiveness for design and rehabilitation of civil infrastructure is rapidly growing unprecedentedly in civil engineering practice. Accordingly, it is expected that the life-cycle cost in the 21st century will become a new paradigm for all engineering decision problems in practice. However, in spite of impressive progress in the researches on the LCC, so far, most researches in Koreahave only focused on roadway bridges, which are not applicable to railway bridges. Thus, this paper presents the formulation models and methods for uncertainty-based LCCA for railroad bridges consideringboth objective statistical data available in the agency database of railroad bridges management and subjective data obtained form interviews with experts of the railway agency, which are used to anew uncertainty-based expected maintenance/repair costs including lifetime indirect costs. For reliable assessment of the life-cycle maintenance/repair costs, statistical analysis considering maintenance history data and survey data including the subjective judgments of railway experts on maintenance/management of railroad bridges, are performed to categorize critical maintenance items and associated expected costs and uncertainty-based deterioration models are developed. Finally, the formulation for simulation-based LCC analysis of railway bridges with uncertainty-based deterioration models are applied to the design-decision problem, which is to select an optimal bridge type having minimum Life-Cycle cost among various railway bridges types such as steel plate girder bridge, and prestressed concrete girder bridge in the basic design phase.

• 유통과학연구
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• 제14권2호
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• pp.41-45
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• 2016

Purpose - Finding an optimal path is an essential component for the design and operation of smart transportation or logistics network. Many applications in navigation system assume that travel time of each link is fixed and same. However, in practice, the travel time of each link changes over time. In this paper, we introduce a new transportation problem to find a latest departing time and delivery path between the two nodes, while not violating the appointed time at the destination node. Research design, data, and methodology - To solve the problem, we suggest a mathematical model based on network optimization theory and a backward search method to find an optimal solution. Results - First, we introduce a dynamic transportation problem which is different with traditional shortest path or minimum cost path. Second, we propose an algorithm solution based on backward search to solve the problem in a large-sized network. Conclusions - We proposed a new transportation problem which is different with traditional shortest path or minimum cost path. We analyzed the problem under the conditions that travel time is changing, and proposed an algorithm to solve them. Extending our models for visiting two or more destinations is one of the further research topics.