• 한국정밀공학회지
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• 제21권9호
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• pp.32-40
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• 2004

This paper deals with an automated computer-aided process planning and die design system by which designer can determine operation sequences even if they have a little experience in process planning and die design for axisymmetric products. An attempt is made to link programs incorporating a number of expert design rules with the process variables obtained by commercial FEM softwares, DEFORM and ANSYS, to form a useful package. The system is composed of four main modules. The process planning and the die design modules consider several factors, such as the complexities of preform geometry, punch and die profiles, specifications of available multi former, and the availability of standard parts. They can provide a flexible process based on either the reduction in the number of forming sequences by combining the possible two processes in sequence, or the reduction of deviation of the distribution on the level of the required forming loads by controlling the forming ratios. Especially in die design module an optimal design technique and horizontal split die were investigated for determining appropriate dimensions of components of multi-former die set. It is constructed that the proposed method can be beneficial for improving the tool life of die set at practice.

• Smart Structures and Systems
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• 제2권2호
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• pp.189-208
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• 2006

Monitoring large-scale civil engineering structures such as offshore platforms and high-large buildings requires a large number of sensors of different types. Innovative sensor data information technologies are very extremely important for data transmission, storage and retrieval of large volume sensor data generated from large sensor networks. How to obtain the optimal sensor set and placement is more and more concerned by researchers in vibration-based SHM. In this paper, a method of determining the sensor location which aims to extract the dynamic parameter effectively is presented. The method selects the number and place of sensor being installed on or in structure by through the tolerance domain statistical inference algorithm combined with second order sensitivity technology. The method proposal first finds and determines the sub-set sensors from the theoretic measure point derived from analytical model by the statistical tolerance domain procedure under the principle of modal effective independence. The second step is to judge whether the sorted out measured point set has sensitive to the dynamic change of structure by utilizing second order characteristic value sensitivity analysis. A 76-high-building benchmark mode and an offshore platform structure sensor optimal selection are demonstrated and result shows that the method is available and feasible.

• 제어로봇시스템학회논문지
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• 제9권5호
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• pp.407-412
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• 2003

An effective methodology is .reported for determining the optimal capacity (lot-size) of batch processing and storage networks which include material recycle or reprocessing streams. We assume that any given storage unit can store one material type which can be purchased from suppliers, be internally produced, internally consumed and/or sold to customers. We further assume that a storage unit is connected to all processing stages that use or produce the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. The objective for optimization is to minimize the total cost composed of raw material procurement, setup and inventory holding costs as well as the capital costs of processing stages and storage units. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory hold-up. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two subproblems. The first yields analytical solutions for determining batch sizes while the second is a separable concave minimization network flow subproblem whose solution yields the average material flow rates through the networks. For the special case in which the number of storage is equal to the number of process stages and raw materials storage units, a complete analytical solution for average flow rates can be derived. The analytical solution for the multistage, strictly sequential batch-storage network case can also be obtained via this approach. The principal contribution of this study is thus the generalization and the extension to non-sequential networks with recycle streams. An illustrative example is presented to demonstrate the results obtainable using this approach.

• 제어로봇시스템학회논문지
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• 제10권6호
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• pp.537-544
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• 2004

An effective methodology is reported for determining the optimal lot size of batch processing and storage networks which include uncertain demand forecasting. We assume that any given storage unit can store one material type which can be purchased from suppliers, internally produced, infernally consumed, transported to or from other sites and/or sold to customers. We further assume that a storage unit is connected to all processing and transportation stages that consume/produce or move the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. A batch transportation process can transfer one material or multiple materials at once between sites. The objective for optimization is to minimize the probability averaged total cost composed of raw material procurement, processing setup, transportation setup and inventory holding costs as well as the capital costs of processing stages and storage units. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two sub-problems. The first yields analytical solutions for determining lot sires while the second is a separable concave minimization network flow subproblem whose solution yields the average material flow rates through the networks for the given demand forecast scenario. The result of this study will contribute to the optimal design and operation of the global supply chain.

• 한국콘텐츠학회논문지
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• 제6권1호
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• pp.23-30
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• 2006

Temporal 데이터의 클러스터링 방법론 중의 하나로 모델기반 방법론이 있다. 이는 각 클러스터에 대하여 오토마타기반의 모델을 가정하는 것이다. 개별 모델을 추출하기 위해서는 먼저 전체 데이터에 대한 적합한 모델을 찾는 것이 필요하다. 전체에 대한 모델은 데이터집합에 대한 최적의 클러스터의 수를 결정함으로 개별 모델 구축의 준비를 완료한다. 본 연구에서는 클러스터 수를 결정하기 위한 기준인 베이지안 정보기준(BIC : Bayesian Information Criterion) 근사법의 활용도를 검증하고 데이터 크기와 BIC 값의 상관관계를 파악함으로 탐색 효율을 높이는 방안을 제안한다. 실험에서는 인위적 모델을 통하여 생성된 인공적인 여러 형태의 데이터집합을 활용하여 BIC근사 측도의 활용성에 대해 살펴보았다. 실험결과에서 보여주는 것처럼 BIC 근사 측도는 데이터의 크기가 비교적 클 경우에 올바른 파티션의 사이즈를 추정함을 확인하였다.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2006년 창립20주년기념 정기학술대회 및 국제워크샵
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• pp.294-297
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• 2006

The rail clamp is the device to prevent the crane slips along a rail from the wind blast as well as to locate a container crane in the set position during an operating mode. In this study we conduct the research for determining the proper position of supporter to prevent the overload applied to the rail clamp with respect to the wedge angle in the wedge type rail clamp. The friction force between the jaw pad and the rail to prevent that the crane slips along a rail, when the wind blows, is generated fly the rail-directional wind load. Accordingly the proper position of the supporter to prevent the overload is determined fly analyzing the forces applied to the rail clamp in the wedge working stage. In order to analyze the effect of the wedge angle on the position of supporter, 5-kinds of wedge angles, such as 2, 4, 6, 8, $10^{\circ}$, were adapted as the design parameter, and the wind speed of 40m/s was adapted as the design wind speed criteria.

• 산업경영시스템학회지
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• 제38권2호
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• pp.120-128
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• 2015

Quality function deployment (QFD) is a useful method in product design and development to maximize customer satisfaction. In the QFD, the technical attributes (TAs) affecting the product performance are identified, and product performance is improved to optimize customer requirements (CRs). For product development, determining the optimal levels of TAs is crucial during QFD optimization. Many optimization methods have been proposed to obtain the optimal levels of TAs in QFD. In these studies, the levels of TAs are assumed to be continuous while they are often taken as discrete in real world application. Another assumption in QFD optimization is that the requirements of the heterogeneous customers can be generalized and hence only one house of quality (HoQ) is used to connect with CRs. However, customers often have various requirements and preferences on a product. Therefore, a product market can be partitioned into several market segments, each of which contains a number of customers with homogeneous preferences. To overcome these problems, this paper proposes an optimization approach to find the optimal set of TAs under multi-segment market. Dynamic Programming (DP) methodology is developed to maximize the overall customer satisfaction for the market considering the weights of importance of different segments. Finally, a case study is provided for illustrating the proposed optimization approach.

• 한국정밀공학회지
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• 제22권5호
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• pp.63-71
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• 2005

When an almost flat surface under test is measured by an interferometer, the measurement result is largely influenced by systematic errors that include geometrical errors of a reference flat surface. To determine the systematic errors of the interferometer by the conventional method that is called the three flat method, we must take the reference flat surface out from the interferometer and measure it. Because of difficulties to set the reference flat surface to the interferometer exactly and quickly, this method is not practical. On the other hand, the method that measures a surface under test with some shifts in the direction being perpendicular to the optical axis of the interferometer is studied. However, the parasitic pitching, rolling and up-down movement caused by the above shifts brings serious error to the measurement result, and the algorithm by which the influences can be eliminated is not still established. In this paper, we propose the self-calibration algorithm for determining the systematic errors that include geometrical errors of a reference flat surface by several rotation shifts and a linear shift of general surface under test, and verify by a numerical experiment that this algorithm is useful for determining the systematic errors.

• 산업경영시스템학회지
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• 제12권19호
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• pp.25-30
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• 1989

This study is concerned with a job sequencing method using the concept of sampling technique. This sampling technique has never been applied to develop the scheduling algorithms. The most job sequencing algorithms have been developed to determine the best or good solution under the special conditions. Thus, it is not only very difficult, but also taken too much time to develop the appropriate job schedules that satisfy the complex work conditions. The application areas of these algorithms are also very narrow. Under these circumstances it is very desirable to develop a simple job sequencing method which can produce the good solution with the short tine period under any complex work conditions. It is called a sampling job sequencing method in this study. This study is to examine the selection of the good job sequence of 1%-5% upper group by the sampling method. The result shows that there is the set of 0.5%-5% job sequence group which has to same amount of performance measure with the optimal job sequence in the case of experiment of 2/n/F/F max. This indicates that the sampling job sequencing method is a useful job sequencing method to find the optimal or good job sequence with a little effort and time consuming. The results of ANOVA show that the two factors, number of jobs and the range of processing time are the significant factors for determining the job sequence at $\alpha$=0.01. This study is extended to 3 machines to machines job shop problems further.

• International Journal of Naval Architecture and Ocean Engineering
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• 제4권1호
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• pp.44-56
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• 2012

Autonomous Underwater Vehicles (AUVs) provide a useful means of collecting detailed oceano-graphic information. The hull resistance of an AUV is an important factor in determining the power requirements and range of the vehicle. This paper describes a procedure using Computational Fluid Dynamics (CFD) for determining the hull resistance of an AUV under development, for a given propeller rotation speed and within a given range of AUV velocities. The CFD analysis results reveal the distribution of the hydrodynamic values (velocity, pressure, etc.) around the AUV hull and its ducted propeller. The paper then proceeds to present a methodology for optimizing the AUV profile in order to reduce the total resistance. This paper demonstrates that shape optimization of conceptual designs is possible using the commercial CFD package contained in Ansys$^{TM}$. The optimum design to minimize the drag force of the AUV was identified for a given object function and a set of constrained design parameters.