• Title/Summary/Keyword: Robust Design Optimization

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A Global Robust Optimization Using the Kriging Based Approximation Model (크리깅 근사모델을 이용한 전역적 강건최적설계)

  • Park Gyung-Jin;Lee Kwon-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.9 s.240
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    • pp.1243-1252
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    • 2005
  • A current trend of design methodologies is to make engineers objectify or automate the decision-making process. Numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, the Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, a design procedure for global robust optimization is developed based on the kriging and global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the function. Robustness is determined by the DACE model to reduce real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. As the postprocess, the first order second-moment approximation method is applied to refine the robust optimum. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

A Study on the Robust Design Using Kriging Surrogate Models (크리깅 근사모델을 이용한 강건설계에 관한 연구)

  • Lee, Kwon-Hee;Cho, Yong-Chul;Park, Gyung-Jin
    • Proceedings of the KSME Conference
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    • 2004.11a
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    • pp.870-875
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    • 2004
  • Current trend of design technologies shows engineers to objectify or automate the given decision-making process. The numerical optimization is an example of such technologies. However, in numerical optimization, the uncertainties are uncontrollable to efficiently objectify or automate the process. To better manage these uncertainties, Taguchi method, reliability-based optimization and robust optimization are being used. To obtain the target performance with the maximum robustness is the main functional requirement of a mechanical system. In this research, the robust design strategy is developed based on the DACE and the global optimization approaches. The DACE modeling, known as the one of Kriging interpolation, is introduced to obtain the surrogate approximation model of the system. The robustness is determined by the DACE model to reduce the real function calculations. The simulated annealing algorithm of global optimization methods is adopted to determine the global robust design of a surrogated model. The mathematical problems and the MEMS design problem are investigated to show the validity of the proposed method.

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A Robust Design Using Approximation Model and Probability of Success (근사모델 및 성공확률을 이용한 강건설계)

  • Song, Byoung-Cheol;Lee, Kwon-Hee
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.7 no.3
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    • pp.3-11
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    • 2008
  • Robust design pioneered by Dr. G. Taguchi has been applied to versatile engineering problems for improving quality. Since 1980s, the Taguchi method has been introduced to numerical optimization, complementing the deficiencies of deterministic optimization, which is often called the robust optimization. In this study, the robust optimization strategy is proposed by considering the robustness of objective and constraint functions. The statistics of responses in the functions are surrogated by kriging models. In addition, objective and/or constraint function is represented by the probability of success, thus facilitating robust optimization. The mathematical problem and the two-bar design problem are investigated to show the validity of the proposed method.

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ROBUST RELIABILITY DESIGN OF VEHICLE COMPONENTS WITH ARBITRARY DISTRIBUTION PARAMETERS

  • Zhang, Y.;He, X.;Liu, Q.;Wen, B.
    • International Journal of Automotive Technology
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    • v.7 no.7
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    • pp.859-866
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    • 2006
  • This study employed the perturbation method, the Edgeworth series, the reliability optimization, the reliability sensitivity technique and the robust design to present a practical and effective approach for the robust reliability design of vehicle components with arbitrary distribution parameters on the condition of known first four moments of original random variables. The theoretical formulae of the robust reliability design for vehicle components with arbitrary distribution parameters are obtained. The reliability sensitivity is added to the reliability optimization design model and the robust reliability design is described as a multi-objection optimization. On the condition of known first four moments of original random variables, the respective program can be used to obtain the robust reliability design parameters of vehicle components with arbitrary distribution parameters accurately and quickly.

A Robust Optimization Using the Statistics Based on Kriging Metamodel

  • Lee Kwon-Hee;Kang Dong-Heon
    • Journal of Mechanical Science and Technology
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    • v.20 no.8
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    • pp.1169-1182
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    • 2006
  • Robust design technology has been applied to versatile engineering problems to ensure consistency in product performance. Since 1980s, the concept of robust design has been introduced to numerical optimization field, which is called the robust optimization. The robustness in the robust optimization is determined by a measure of insensitiveness with respect to the variation of a response. However, there are significant difficulties associated with the calculation of variations represented as its mean and variance. To overcome the current limitation, this research presents an implementation of the approximate statistical moment method based on kriging metamodel. Two sampling methods are simultaneously utilized to obtain the sequential surrogate model of a response. The statistics such as mean and variance are obtained based on the reliable kriging model and the second-order statistical approximation method. Then, the simulated annealing algorithm of global optimization methods is adopted to find the global robust optimum. The mathematical problem and the two-bar design problem are investigated to show the validity of the proposed method.

Robust Optimization of a Lens System for a Mobile Phone Camera (휴대폰 카메라용 렌즈 시스템의 강건최적설계)

  • Jung, Sang-Jin;Min, Jun-Hong;Choi, Dong-Hoon;Kim, Ju-Ho
    • Korean Journal of Computational Design and Engineering
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    • v.15 no.5
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    • pp.325-332
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    • 2010
  • A lens system for mobile phone cameras is comprised of various lenses and designed so as to satisfy design requirements for responses such as a modular transfer function (MTF). However, it is difficult to manufacture and assemble camera modules to maintain the same performance compared with the designed camera modules, because of uncertainty. We should always design a lens system by considering uncertainty that can be caused by errors in the manufacturing and assembly process of mobile phone cameras. The robust optimization offers tools of making robust decisions with the consideration of design parameters, uncontrollable parameters, and the variance of the system. Using an efficient reliability analysis method and an optimization algorithm, we obtained robust optimization results that maximize the mean of MTF and minimize the standard deviation and proposed a new robust design process for a lens system.

Design of Annular Finned Heat Transfer Tube Using Robust Optimization (원형 확장 휜 열 교환기의 치수 강건최적설계)

  • Jhong, Woo-Jin;Yoon, Ji-Won;Lee, Jong-Soo
    • 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.

Simultaneous Optimization Using Loss Functions in Multiple Response Robust Designs

  • Kwon, Yong Man
    • Journal of Integrative Natural Science
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    • v.14 no.3
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    • pp.73-77
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    • 2021
  • Robust design is an approach to reduce the performance variation of mutiple responses in products and processes. In fact, in many experimental designs require the simultaneous optimization of multiple responses. In this paper, we propose how to simultaneously optimize multiple responses for robust design when data are collected from a combined array. The proposed method is based on the quadratic loss function. An example is illustrated to show the proposed method.

Probabilistic Structure Design of Automatic Salt Collector Using Reliability Based Robust Optimization (신뢰성 기반 강건 최적화를 이용한 자동채염기의 확률론적 구조설계)

  • Song, Chang Yong
    • Journal of the Korean Society of Industry Convergence
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    • v.23 no.5
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    • pp.799-807
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    • 2020
  • This paper deals with identification of probabilistic design using reliability based robust optimization in structure design of automatic salt collector. The thickness sizing variables of main structure member in the automatic salt collector were considered the random design variables including the uncertainty of corrosion that would be an inevitable hazardousness in the saltern work environment. The probabilistic constraint functions were selected from the strength performances of the automatic salt collector. The reliability based robust optimum design problem was formulated such that the random design variables were determined by minimizing the weight of the automatic salt collector subject to the probabilistic strength performance constraints evaluating from reliability analysis. Mean value reliability method and adaptive importance sampling method were applied to the reliability evaluation in the reliability based robust optimization. The three sigma level quality was considered robustness in side constraints. The probabilistic optimum design results according to the reliability analysis methods were compared to deterministic optimum design results. The reliability based robust optimization using the mean value reliability method showed the most rational results for the probabilistic optimum structure design of the automatic salt collector.

Study of Reliability-Based Robust Design Optimization Using Conservative Approximate Meta-Models (보수적 근사모델을 적용한 신뢰성 기반 강건 최적설계 방법)

  • Sim, Hyoung Min;Song, Chang Yong;Lee, Jongsoo;Choi, Ha-Young
    • Journal of Ocean Engineering and Technology
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    • v.26 no.6
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    • pp.80-85
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    • 2012
  • The methods of robust design optimization (RDO) and reliability-based robust design optimization (RBRDO) were implemented in the present study. RBRDO is an integrated method that accounts for the design robustness of an objective function and for the reliability of constraints. The objective function in RBRDO is expressed in terms of the mean and standard deviation of an original objective function. Thus, a multi-objective formulation is employed. The regressive approximate models are generated via the moving least squares method (MLSM) and constraint-feasible moving least squares method (CF-MLSM), which make it possible to realize the feasibility regardless of the multimodality/nonlinearity of the constraint function during the approximate optimization processes. The regression model based RBRDO is newly devised and its numerical characteristics are explored using the design of an actively controlled ten bar truss structure.