• Journal of Korean Institute of Industrial Engineers
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• v.38 no.3
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• pp.198-207
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• 2012

In product or process parameter design, the case of multiple performance characteristics appears more commonly than that of a single characteristic. Numerous methods have been developed to deal with such multi-characteristic parameter design (MCPD) problems. Among these, this paper considers three representative methods, which are respectively based on the desirability function (DF), grey relational analysis (GRA), and principal component analysis (PCA). These three methods are then used to solve the MCPD problems in ten case studies reported in the literature. The performance of each method is evaluated for various combinations of its algorithmic parameters and alternatives. Relative performances of the three methods are then compared in terms of the significance of a design parameter and the overall performance value corresponding to the compromise optimal design condition identified by each method. Although no method is significantly inferior to others for the data sets considered, the GRA-based and PCA-based methods perform slightly better than the DF-based method. Besides, for the PCA-based method, the compromise optimal design condition depends much on which alternative is adopted while, for the GRA-based method, it is almost independent of the algorithmic parameter, and therefore, the difficulty involved in selecting an appropriate algorithmic parameter value can be alleviated.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.7
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• pp.945-950
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• 2002

Shape optimization of a flow system is done to obtain the required effects, in the engineering fields. Most of these designs are accomplished by empirical or numerical analysis. In empirical analysis, it is difficult to obtain an optimal shape in the feasible design region. And, in numerical method, it usually needs much calculation expenses for shape optimization, because of design sensitivity analysis. In this study, we used the growth-strain method having only one distributed parameter such as a design variable. It optimizes a shape by making a distributed parameter such as dissipation energy uniform in a flow system, and then applied to two-flow systems. In order to overcome the stability occurred in numerical analysis performed by Azegami, the equation of volumic strain has been modified. Also, the shapes were compared with the known optimal shapes for the flow systems. Consequently, we confirm that the modified growth-strain method is very efficient and practical in shape optimization of the flow systems.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.9
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• pp.9-17
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• 1999

This investigation is the result of the structural analysis by finite element method for optimal design of the cross beam with circular holes of the electric car-body. in order to install the air pipe and electric wire pipe that correspond signal between electric machines for the control system and to reduce the weight of the electric car-body, several circular areas from a cross beam should be taken off. What we want to perform is the optimal design of a cross beam with circular holes to posses equal stress in comparison with no hole cross beam. first, no hole cross beam as basic modal be chosen, executing the analysis, reviewing the distribution of stress and displacement at each location. several parameter should be adopted from the cross beam geometry like the location and shape of the hole to affect the maximum stress and displacement. So the analysis was executed by finite element analysis for finding optimal design parameter to the change of the location and shape of the circular hole. finally, the optimal design of the cross beam with circular holes was obtained and the maximum equivalent stress was compared with no hole cross beam at each location.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.672_673
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• 2009

In this paper seeks the parameter which relates with the efficiency from premium efficiency level single-phase induction motor. Also it compares with the parameters and it analyzes and an optimum parameter it seeks by FEM. Consquently, a optimal design is accomplished from the this paper. Also parameters compare efficiency. And it analyzes and studies about optimum parameter by FEM. The sample single-phase induction motor selection selected existing premium level motor. We analyze each parameter using 2-D finite element analysis (FEM). According to Study of losses and Design flow, losses and efficiency can be explain by many parameter. So this paper present optimal parameters. Finally, this paper presents the method which raises the efficiency of premium efficiency level single-phase induction motor.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.2
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• pp.66-73
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• 1997

In many optimal methods for the structural design, the structural analysis is performed with the given design parameters. Then the design sensitivity is calculated based on its structural anaysis results. There-after, the design parameters are changed iteratively. But genetic algorithm is a optimal searching technique which is not depend on design sensitivity. This method uses for many design para- meter groups which are generated by a designer. The generated design parameter groups are become initial population, and then the fitness of the all design parameters are calculated. According to the fitness of each parameter, the design parameters are optimized through the calculation of reproduction process, degradation and interchange, and mutation. Those are the basic operation of the genetic algorithm. The changing process of population is called a generation. The basic calculation process of genetic algorithm is repeatly accepted to every generation. Then the fitness value of the element of a generation becomes maximum. Therefore, the design parameters converge to the optimal. In this study, the optimal design pro- cess of a machine tool structure for static loading is presented to determine the optimal base supporting points and structure thickness using a genetic algorithm.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.6
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• pp.1464-1473
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• 1990

Optimal design parameters are estimated from the sensitivity function and performance index variation. Suspension design modification for performance improvement and basic materials for practical applications are presented. The linear quarter model of a vehicle suspension is analyzed in order to represent the utilities of sensitivity analysis, and sensitivity function is determined in the frequency domain. The change of frequency response function is predicted, which depends on the design parameter variation and the property is verified by computer simulation. As an investigation results of sensitivity function for the vibrational amplitude of sprung mass to road profile input, it is shown that the most sensitive parameters are the suspension damping and the suspension stiffness. In order to identify the effects of these two parameters to the performance of suspension system, the performance index variation according to the changes of parameters is considered and then optimal design parameters are determined. It is verified that the system response is improved noticeably in the both of frequency and time domain after the design modification with the optimal parameters.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.135-141
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• 2009

A variety of statistical methods are applied to model and optimize responses, related to product or system's quality, in terms of control and noise factors at design and manufacturing stages. Most of them assume continuous response variables but, assessing the performance of a product or system often involves categorical observations, such as ratings and scores. Although most previous works to deal with the categorical data provide sorhisticated response models and ensure unbiased outcomes, they require heavy computation to estimate the model parameters, as well as enough replications. In this study, we present some practical approaches for optimal parameter design with ordered categorical response when only a few or no replication is available. Two real-life examples are given to illustrate the presented methods.

• Proceedings of the Safety Management and Science Conference
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• 2000.11a
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• pp.251-254
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• 2000

The critical problem in dealing with multiple characteristics is how to compromise the conflict among the selected levels of the design parameters for each individual characteristic. In this study, First, Methodology using SN ratio optimized by univariate technique is proposed and a parameter design procedure to achieve the optimal compromise among several different response variables is developed. Second, to solve the issue on the optimal design for multiple quality characteristics, this study modelled the expected loss function with cross-product terms among the characteristics and derived range of the coefficients of the terms. The model will be used to determine the global optimal design parameters where there exists the conflict among the characteristics, which shows difference in optimal design parameters for the individual characteristics. Third, this paper propose a decision model to incorporates the values assigned by a group of experts on different factors in weighting decision of characteristic. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for weighting decision of characteristic.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.737-741
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• 2003

The wind power system is spotlighted as one of the no-pollution power generation systems. The system uses winds as power source that are rotated the blade and the rotating power from blade generate the electricity power. Gearbox needs to transfer the wind powers that have the high-torque-low-speed characteristics to generator that have the low-torque-high-speed characteristics. Because the wind power system generally locates the remote place like seaside or mountainside and the gearbox installs on the limited and high placed space, the gearbox of the wind power system is required the optimal space design and high reliability. In this paper, the structure of the gearbox is proposed to achieve the optimal space and efficiency by compounding the planetary gear train that has the high power density and parallel type gear train that has the long service life. The design parameters that are affected the service life are studied. The gear ratio and face width are investigated as an affected parameter for design sensitivity of service life.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1460-1463
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• 1997

The aim of this paper is to suggest a design method of the model following optimal boiler-turbine H.inf. control system using genetic algorithm. This boiler-turbine H.inf. control system is designed by applying genetic algortihm with reference model to the optimal determination of weighting functions and design parameter .gamma. that are given by Glover-Doyle algornithm whch can design H.inf. contrlaaer in the sate. space. The first method to do this is ghat the gains of weightinf functions and .gamma. are optimized simultaneously by genetic algroithm. And the second method is that not only the gains and .gamma. but also the dynamics of weighting functions are optimized at the same time by genetic algonithm. The effectiveness of this boiler-turbine H.inf. control system is verified and compared with LQG/LTR control system by computer simulation.