• Title/Summary/Keyword: Robust design

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A Review of Robust Design Methodologies (강건설계기법의 연구동향)

  • Park, Gyung-Jin;Lee, Tae-Hee;Lee, Kwon-Hee;Hwang, Kwang-Hyeon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.28 no.9
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    • pp.1368-1383
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    • 2004
  • Robust design has been developed with the expectation that an insensitive design can be realized. That is, a product designed by robust design should be insensitive to external noises or tolerances. Robust design can be classified into three methods: (1) The Taguchi method (2) robust optimization (3) robust design by the axiomatic approach. In this paper, each method is reviewed and investigated. Pros and cons fur each method are discussed and a future direction for development is proposed.

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.

Robust Optimal Damper Design of Structures with Modal Uncertainty Using Multi-Objective System Identification (다목적 시스템식별을 이용한 모우드 불확실성이 있는 구조물의 강인 최적 감쇠기 설계)

  • Jeong, Seong-Woon;Ok, Seung-Yong;Park, Won-Suk;Koh, Hyun-Moo
    • Journal of the Korean Society of Safety
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    • v.27 no.1
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    • pp.76-85
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    • 2012
  • This paper proposes a robust damper design technique for adjacent structures against model uncertainty. This approach introduces multi-objective optimization based system identification using measurement information which enables reasonable selection of the perturbation range in the robust design. Moreover, in order to improve the numerical efficiency in sampling the structural models required for the robust design of large structures, we define new objective functions which enable us to minimize the number of candidate models suitable to the purpose of the robust design. In addition, the performance index is newly employed to evaluate the robust performance of the sampled structural models, and the robust design has been performed according to the performance index. As a numerical example to demonstrate the efficiency of the proposed method, 5-story and 10-story two adjacent buildings are taken into account, and the existing and newly proposed robust design approaches are compared with each other. The results demonstrate that the proposed approach can guarantee more robust damper system only using small number of samples of the structural models because of using the measurement information which leads to improvement in the numerical efficiency, compared with the existing robust design methods.

Robust Optimization of a Resonant-type Micro-probe Using Gradient Index Based Robust Optimal Design Method (구배 지수에 근거한 강건 최적 설계 기법을 이용한 공진형 미소탐침의 강건 최적화)

  • Han, Jeong-Sam;Kwak, Byung-Man
    • 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.

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Design of a Robust Target Tracker for Parameter Variations and Unknown Inputs

  • Kim, Eung-Tai;Andrisani, D. II
    • International Journal of Aeronautical and Space Sciences
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    • v.2 no.2
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    • pp.73-81
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    • 2001
  • This paper describes the procedure to develop a robust estimator design method for a target tracker that accounts for both structured real parameter uncertainties and unknown inputs. Two robust design approaches are combined: the Mini-p-Norm. design method to consider real parameter uncertainties and the $H_{\infty}$ design technique for unknown disturbances and unknown inputs. Constant estimator gains are computed that guarantee the robust performance of the estimator in the presence of parameter variations in the target model and unknown inputs to the target. The new estimator has two design parameters. One design parameter allows the trade off between small estimator error variance and low sensitivity to unknown parameter variations. Another design parameter allows the trade off between the robustness to real parameter variations and the robustness to unknown inputs. This robust estimator design method was applied to the longitudinal motion tracking problem of a T-38 aircraft.

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A Study on Linear Matrix Inequalities Robust Active Suspension Control System Design Algorithm

  • Park, Jung-Hyen
    • Journal of information and communication convergence engineering
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    • v.6 no.1
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    • pp.105-109
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    • 2008
  • A robust optimal control system design algorithm in active suspension equipment adopting linear matrix inequalities control system design theory is presented. The validity of the linear matrix inequalities robust control system design in active suspension system through the numerical examples is also investigated.

Robust Design of a Discrete System Using Taguchi's Standard Signal-to-Noise Ratio (다구치의 표준 SN비를 이용한 이산형 시스템의 로버스트설계)

  • Kim, Seong-Jun
    • Journal of Korean Society for Quality Management
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    • v.27 no.2
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    • pp.101-111
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    • 1999
  • The purpose of Taguchi's robust design lies in quality improvement by making the performance of a system robust against noise. Robust design with continuous performance characteristics has been the subject of much interest. However relatively little work has been done for discrete characteristics such as 0-1, good-medium-bad, etc. This paper is concerned with robust design of a discrete dynamic system. We first investigate the Taguchi method for robust design with discrete dynamic characteristics and discuss his standard error probability (SEP). Then we propose a generalized SEP, which makes it possible to encompass a wider class of robust design problems. An illustration is also given by example.

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Robust Optimization of Automotive Seat by Using Constraint Response Surface Model (제한조건 반응표면모델에 의한 자동차 시트의 강건최적설계)

  • 이태희;이광기;구자겸;이광순
    • 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.

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Robust Design of Mechanisms Using the Response Surfae Analysis (반응표면분석법을 이용한 기구의 강건설계)

  • 한형석;박태원
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1996.04a
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    • pp.743-748
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    • 1996
  • In this study a method for a robust design of mechanisms is proposed. The method used in the experimental anlysis and quqlity engineering is applied for mechanisms design. A mathematical model for a mechanism is estimated by the responese surface analysis and the robust design can be carried out. The method can be applied for mechanisms generally. Furthermore because the method can be used in the design stage using the computer model, improved quality and lower cost of the product is achieved even in the design stage.

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Robust Parameter Design for Multiple Quality Characteristics using Factor Analysis

  • Kwon, Yong-Man;Chang, Duk-Joon
    • 한국데이터정보과학회:학술대회논문집
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    • 2004.04a
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    • pp.131-139
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    • 2004
  • Robust parameter design is to identify appropriate settings of control factors that make the system's performance robust to changes in the noise factors that represent the source of variation. In this paper, we introduce a factor analysis approach to simultaneously optimize multiple quality characteristics in the robust parameter design. An example is illustrated to compare it with already proposed method.

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