• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.71-75
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• 1994

This paper presents a method of optimal design of an automatic transfer system which is controlled by the electro-pneumatic servo scheme. The electro-pneumatic automatic transfer system can move parts to desired points or displace defective parts. The dynamic performance of the system can be examined by observing the behavior of the output. The output of the servo control system is the motion of the cylinder, pneumatic actuator. The dynamic performance of the cylinder is governed by the parameters of the components of the entire system. The optimal design can be accomplished by selecting of the parameters such that the desired dynamic performance of the cylinder is obtained. The optimal set of parameters might be obtained through the repeated simulations. Repeated simulations, however, is not effective to determine the optimal set of parameters since the set of parameters is large. This paper presents modeling, application of an optimization method, and the numerical results. The optimization algorithm utilizes the concept of the conjugate gradient method. The results show that the suggested optimization scheme can render faster convergence of iteration compared to other method based on an algebraic optimization method and can reduce the design efforts.

• International Journal of Control, Automation, and Systems
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• v.5 no.5
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• pp.515-525
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• 2007

In this paper, we develop a co-design methodology of stochastic optimal controllers and network parameters that optimizes the overall quality of control (QoC) in networked control systems (NCSs). A new dynamic model for NCSs is provided. The relationship between the system stability and performance and the sampling frequency is investigated, and the analysis of co-design of control and network parameters is presented to determine the working range of the sampling frequency in an NCS. This optimal sampling frequency range is derived based on the system dynamics and the network characteristics such as data rate, time-delay upper bound, data-packet size, and device processing time. With the optimal sampling frequency, stochastic optimal controllers are designed to improve the overall QoC in an NCS. This co-design methodology is a useful rule of thumb to choose the network and control parameters for NCS implementation. The feasibility and effectiveness of this co-design methodology is verified experimentally by our NCS test bed, a ball magnetic-levitation (maglev) system.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.1307-1312
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• 2009

Design is an act based on multidisciplinary information. The involvement of various stakeholders makes it difficult to process, plan, and integrate. Iteration is frequent in most of the engineering design and development projects including construction. Design iterations cause rework, and extra efforts are required to get the optimal sequence and to manage the projects. The simple project management techniques are insufficient to fulfill the requirements of integrated design. This paper entails two things: design structure matrix and design parameters' information based model. The emphasis has been given to optimal sequence and crucial iteration using design structure matrix analysis technique. The design projects have been studied using survey data from industry. The optimal sequence and crucial iterations results have been utilized for proposed model. Model integrates two things: information about produced- required key design parameters and information of design changes during the design process. It will help to get familiar with Design management in order to fulfill contemporary needs.

• 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 Mechanical Science and Technology
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• v.17 no.1
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• pp.40-47
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• 2003

In this paper, we constructed the analytic model of control valve as a function of electric and geometric parameters, and analyzed the influence of the design parameters on the dynamic characteristics. For improving the dynamic characteristics, optimal design is conducted by applying sequential quadratic programming method to the analytic model. This optimal design aims to minimize the response time and maximize force efficiency. By this procedure, control valve can be designed to have fast response in motion.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.6
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• pp.799-806
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• 2004

This paper presents a scheme for finding an optimal combination of design parameters affecting on the handling performance of a large truck using design of experiments. The average of the sum of peak-to-peak roll angles at the first and second part of the double lane is used as an objective function for design of experiments. Six design parameters are selected from all possible parameters affecting on the handling performance. The table of orthogonal arrays is made by 27 times simulations. A computational model of a large truck is developed by MSC/NASTRAN and MSC/ADAMS, and verified the reliability of it with the results of vehicle tests performed in a double lane change course. It is used for the simulations. Analyses of variance and factor effect of the table of orthogonal arrays are performed. This paper proposes an optimal combination of those six design parameters for improving the handling performance of the large truck.

• Journal of the Korean Society for Precision Engineering
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• v.24 no.3 s.192
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• pp.76-83
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• 2007

The Taguchi method is applied to obtain the optimal design of an automotive pedal arm in consideration of the stiffness test specification. Design parameters are defined to describe shape of the pedal arm. Volume, maximum Von-Mises stress and maximum displacement of the pedal arm are established as the smaller-the-better characteristics. Optimal parameters are determined on the basis of the analyzed level averages of the characteristics.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.4
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• pp.427-433
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• 2013

Stair climbing is one of critical issues for field robots to widen applicable areas. This paper presents optimal design on kinematic parameters of a new robotic platform for stair climbing. The robotic platform climbs various stairs by body-flip locomotion with caterpillar type main platform. Kinematic parameters such as platform length, platform height, and caterpillar rotation speed are optimized to maximize stair-climbing stability. Three types of stairs are used to simulate typical user conditions. The optimal design process is conducted based on Taguchi methodology, and resulting parameters with optimized objective function are presented. In near future, a prototype is assembled for real environment testing.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.6
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• pp.28-34
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• 2008

Mg alloy is widely used for the IT, auto and consumer electronics industries. Semi-solid casting(SSC) of magnesium alloys is used to produce high quality components. SSC process is analogous with the injection molding of plastics. The high strength and low weight characteristics of magnesium alloys render the high-precision fabrication of thin-walled components with large surface areas. To produce thin-walled magnesium alloy parts, SSC process parameters on the quality of the finished product should be clearly studied. In this paper, to select optimal process parameters, Taguchi method is applied to the optimal design of the process parameters in the SSC process. The die temperature, injection velocity and barrel temperature of the SSC process are selected for the process parameters. The effectiveness of the optimal design is verified through the CAE software.