• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.113-120
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• 2007

Design optimization of layered plates bonding process is conducted by considering uncertainties in a manufacturing process, in order to reduce the crack failure arising due to the residual stress at the surface of the adherent which is caused by different thermal expansion coefficients. Robust optimization is peformed to minimize the mean as well as its variance of the residual stress, while constraining the distortion as well as the instantaneous maximum stress under the allowable reliability limits. In this optimization, the dimension reduction (DR) method is employed to quantify the reliability such as mean and variance of the layered plate bonding. It is expected that the DR method benefits the optimization from the perspectives of efficiency, accuracy, and simplicity. The obtained robust optimal solution is verified by the Monte Carlo simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.9
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• pp.1437-1443
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• 2003

Most optimization problems do not consider tolerance of design variables and design parameters. Ignorance of these tolerances may not fit for the practical problems and can lead to an unexpected conclusion. That is why we suggest robust optimization considering tolerances in both design variables and problem parameters. Using robust optimization, we designed minimum weight annular finned heat transfer tube subject to constraints on limitation of pressure difference and minimum value of total heat transfer. Consequently, robust optimization satisfies tolerance considered practical problems.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1254-1261
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• 2003

In this paper we present a simple and efficient robust optimal design formulation and its application to a resonant-type micro probe. The basic idea is to use the Gradient Index (GI) to improve robustness of the objective and constraint functions. In the robust optimal design procedure, a deterministic optimization for performance of MEMS structures is followed by design sensitivity analysis with respect to uncertainties such as fabrication errors and change of operating conditions. During the process of deterministic optimization and sensitivity analysis, dominant performance and uncertain variables are identified to define GI. The GI is incorporated as a term of objective and constraint functions in the robust optimal design formulation to make both performance and robustness improved. While most previous approaches for robust optimal design require statistical information on design variations, the proposed GI based method needs no such information and therefore is cost-efficient and easily applicable to early design stages. For the micro probe example, robust optimums are obtained to satisfy the targets for the measurement sensitivity and they are compared in terms of robustness and production yield with the deterministic optimums through the Monte Carlo simulation.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.1
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• pp.29-34
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• 2008

The efforts of reflecting the system's uncertainties in design step have been made and robust optimization or reliability-based design optimization are examples of the most famous methodologies. In their formulation, the mean and standard deviation of a performance function and constraints expressed by probability conditions are involved. Therefore, it is essential to effectively and accurately calculate them and, in addition, the sensitivity results are required to obtain when the nonlinear programming is utilized during optimization process. We aim to obtain the new and efficient sensitivity formulation, which is based on integral form, on statistical moments such as the mean and standard deviation, and probability constraints. It does not require the additional functional calculation when statistical moments and failure or satisfaction probabilities are already obtained at a design point. Moreover, some numerical examples have been calculated and compared with the exact solution or the results of Monte Carlo Simulation method. The results seem to be very satisfactory.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2000.04b
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• pp.168-173
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• 2000

Design of experiments is utilized for exploring the design space and for building response surface models in order to facilitate the effective solution of multi-objective optimization problems. Response surface models provide an efficient means to rapidly model the trade-off among many conflicting goals. In robust design, it is important not only to achieve robust design objectives but also to maintain the robustness of design feasibility under the effects of variations, called uncertainties. However, the evaluation of feasibility robustness often needs a computationally intensive process. To reduce the computational burden associated with the probabilistic feasibility evaluation, the first-order Taylor series expansions are used to derive individual mean and variance of constraints. For robust design applications, these constraint response surface models are used efficiently and effectively to calculate variances of constraints due to uncertainties. Robust optimization of automotive seat is used to illustrate the approach.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.5
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• pp.1674-1682
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• 1991

본 연구에서는 4기통 고속 가솔린 기관의 흡기관 내 유체유동이 체적효율에 미치는 동적효과를 고려하여, 흡기관에 임피던스를 이용한 음향학적 방법을 이용해서 흡기관 최적설계를 해석하고, 기관실험을 통해 그 신뢰성을 확인하고자 한다.

• Journal of Advanced Technology Convergence
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• v.2 no.2
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• pp.9-14
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• 2023

This study is shown the result of the first year to develop an export 1050MPa-class lightweight ductile iron castings Austempered control arm through the research process to obtain the following results. First, the structure of the optimal design Layout design and development of the component, and then achieve them through the Control Arm rigidity and optimal structure design and robust design of the focus areas of the expected stress Control Arm. Second, to develop a Control Arm reflects the high rigidity and high performance lightweight structures. Control Arm them developed to meet the design and rigidity as required by the consumer through the hollow, and to develop a process for the Core. Third, through optimum alloy composition and heat treatment methods will be derived to derive the amount of iron alloy (Cu, Ni, Mo) and Austempered heat treated and tempered condition. Fourth, through the development of optimum molding technology development component to develop the optimum ADI for the low-stiffness, high-rigidity component development, it attempts to develop a high-strength casting forming technology..

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.561-571
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• 2015

When we consider an optimal design to predict the response corresponding to the point outside the design region, we are extremely careful about choosing the design criteria for selecting the support points. The assumed model and its accompanying error structure should be assumed to extend beyond the design region for the selected design criteria to be valid. Thus, we modify the existing design criteria such as extrapolation-optimality to be suited to those situations. We propose some maximin approaches in this paper. Simple and quadratic regression models are tested to find the basic characteristics of such maximin approaches. Some main findings are discussed in the conclusion.

• Journal of KSNVE
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• v.6 no.1
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• pp.35-44
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• 1996

This paper presents a new type of fuzzy-sliding mode controller for robust tip position control of a single-link flexible manipulator subjected to parameter variations. A sliding mode controller is formulated with an assumption that imposed parameter variations are bounded so that certain deterministic performance can be guaranted. In the design of the sliding mode controller, so called moving sliding surface is adopted to minimize the reaching phase and thus mitigate system sensitivity to the variations. The sliding mode controller is then incorporated with a fuzzy technique to reduce inherently ever-existing chattering which is impediment in position control of flexible manipulators. A set of fuzzy parameters and control rules are obtained from a relation between predetermined sliding surface and representative points in the state space. Computer simulations are undertaken in order to demonstrate superior control performance of the proposed methodology.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.1
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• pp.112-123
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• 1997

The optimization techniques have been applied to versatile engineering problems for reducing manufacturing cost and for automatic design. The deterministic approaches or op5imization neglect the effects on uncertainties of design variables. The uncertainties include variation or perturbation such as tolerance band. The optimum may be useless when the constraints considering worst cases of design variables can not be satisfied, which results from constraint variation. The variation of design variables can also give rise to drastic change of performances. The two issues are related to constraint feasibility and insensitive performance. Robust design suggested in the present study is developed to gain an optimum insensitive to variation on design variables within feasible region. The multiobjective function is composed to the mean and the standard deviation of original objective function, while the constraints are supplemented by adding penalty term to original constraints. This method has a advantage that the second derivatives of the constraints are not required. A mathematical problem and several standard problems for structural optimization are solved to check out the usefulness of the suggested method.