• Title, Summary, Keyword: response surface

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A Measure for Evaluating the Effect of Blocking in Response Surface Designs Using Cuboidal Regions (입방형 영역을 사용한 반응표면계획에서 블록효과를 평가하기 위한 측도)

  • 박상현;장대흥
    • Journal of the Korean Society for Quality Management
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    • v.27 no.1
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    • pp.59-79
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    • 1999
  • The fitting of a response surface model and the subsequent exploration of the response surface are usually based on the assumption that the experimental runs are carried out under homogeneous conditions. This, however, may be quite often difficult to achieve in many experiments. To control such an extraneous source of variation, the response surface design should be arranged in several blocks within which homogeneity of conditions can be maintained. In this case, when fitting a response surface model, the least squares estimates of the model's parameters and the prediction variance will generally depend on how the response surface design is blocked. That is, the choice of a blocking arrangement for a response surface design can have a considerable effect on estimating the mean response and on the size of the prediction variance. In this paper, we propose a measure for evaluating the effect of blocking of response surface designs using cuboidal regions.

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A Study on Process Optimization Using Partial Least Squares Response Surface Function (편최소제곱 반응표면함수를 이용한 공정 최적화에 관한 연구)

  • Park, Sung-Hyun;Choi, Um-Moon;Park, Chang-Soon
    • Journal of the Korean Society for Quality Management
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    • v.27 no.2
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    • pp.237-250
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    • 1999
  • Response surface analysis has been a popular tool conducted by engineers in many processes. In this paper, response surface function, named partial least squares response surface function is proposed. Partial least squares response surface function is a function of partial least squares components and the response surface modeling is used in either a first-order or a second-order model. Also, this approach will have the engineers be able to do the response surface modeling and the process optimization even when the number of experimental runs is less than the number of model parameters. This idea is applied to the nondesign data and an application of partial least squares response surface function to the process optimization is considered.

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Derivation of a Simplified Measure of Slope Rotatability for a Particular Class of Response Surface Designs

  • Kim, Hyuk Joo;Park, Sung Hyun;Kim, Tae-Sung
    • Communications for Statistical Applications and Methods
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    • v.11 no.3
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    • pp.563-574
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    • 2004
  • Slope rotatability of response surface designs is a desirable property when we are interested in estimating slopes of response surfaces. In this paper, we derive a simplified measure of slope rotatability from new viewpoints for response surface designs that are frequently used in response surface methodology.

A new high-order response surface method for structural reliability analysis

  • Li, Hong-Shuang;Lu, Zhen-Zhou;Qiao, Hong-Wei
    • Structural Engineering and Mechanics
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    • v.34 no.6
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    • pp.779-799
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    • 2010
  • In order to consider high-order effects on the actual limit state function, a new response surface method is proposed for structural reliability analysis by the use of high-order approximation concept in this study. Hermite polynomials are used to determine the highest orders of input random variables, and the sampling points for the determination of highest orders are located on Gaussian points of Gauss-Hermite integration. The cross terms between two random variables, only in case that their corresponding percent contributions to the total variation of limit state function are significant, will be added to the response surface function to improve the approximation accuracy. As a result, significant reduction in computational cost is achieved with this strategy. Due to the addition of cross terms, the additional sampling points, laid on two-dimensional Gaussian points off axis on the plane of two significant variables, are required to determine the coefficients of the approximated limit state function. All available sampling points are employed to construct the final response surface function. Then, Monte Carlo Simulation is carried out on the final approximation response surface function to estimate the failure probability. Due to the use of high order polynomial, the proposed method is more accurate than the traditional second-order or linear response surface method. It also provides much more efficient solutions than the available high-order response surface method with less loss in accuracy. The efficiency and the accuracy of the proposed method compared with those of various response surface methods available are illustrated by five numerical examples.

Multi-Level Response Surface Approximation for Large-Scale Robust Design Optimization Problems (다층분석법을 이용한 대규모 파라미터 설계 최적화)

  • Kim, Young-Jin
    • Korean Management Science Review
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    • v.24 no.2
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    • pp.73-80
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    • 2007
  • Robust Design(RD) is a cost-effective methodology to determine the optimal settings of control factors that make a product performance insensitive to the influence of noise factors. To better facilitate the robust design optimization, a dual response surface approach, which models both the process mean and standard deviation as separate response surfaces, has been successfully accepted by researchers and practitioners. However, the construction of response surface approximations has been limited to problems with only a few variables, mainly due to an excessive number of experimental runs necessary to fit sufficiently accurate models. In this regard, an innovative response surface approach has been proposed to investigate robust design optimization problems with larger number of variables. Response surfaces for process mean and standard deviation are partitioned and estimated based on the multi-level approximation method, which may reduce the number of experimental runs necessary for fitting response surface models to a great extent. The applicability and usefulness of proposed approach have been demonstrated through an illustrative example.

Improved Response Surface Method Using Modified Selection Technique of Sampling Points (개선된 평가점 선정기법을 이용한 응답면기법)

  • 김상효;나성원;황학주
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • pp.248-255
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    • 1993
  • Recently, due to the increasing attention to the structural safety under uncertain environments, many researches on the structural reliability analysis have been peformed. Some useful methods are available to evaluate performance reliability of structures with explicit limit states. However, for large structures, in which structural behaviors can be analyzed with finite element models and the limit states are only expressed implicitly, Monte-Carlo simulation method has been mainly used. However, Monte-Carlo simulation method spends too much computational time on repetitive structural analysis. Many alternative methods are suggested to reduce the computational work required in Monte-Carlo simulation. Response surface method is widely used to improve the efficiency of structural reliability analysis. Response surface method is based on the concept of approximating simple polynomial function of basic random variables for the limit state which is not easily expressed in explicit forms of design random variables. The response surface method has simple algorithm. However, the accuracy of results highly depends on how properly the stochastic characteristics of the original limit state has been represented by approximated function, In this study, an improved response surface method is proposed in which the sampling points for creating response surface are modified to represent the failure surface more adequately and the combined use of a linear response surface function and Rackwitz-Fiessler method has been employed. The method is found to be more effective and efficient than previous response surface methods. In addition more consistent convergence is achieved, Accuracy of the proposed method has been investigated through example.

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The Optimization of Bank Branches Efficiency by Means of Response Surface Method and Data Envelopment Analysis: A Case of Iran

  • Shadkam, Elham;Bijari, Mehdi
    • The Journal of Asian Finance, Economics, and Business
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    • v.2 no.2
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    • pp.13-18
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    • 2015
  • In this paper the DRC model is presented for solving multi objective problem. The proposed model is a combination of data envelopment analysis, Cuckoo algorithm and the response surface method. Due to reasons like costs, time and irreversible damages, it is not possible to analyze each and every one of the proposed models in practice, so the simulation is used. Since the number of experiments for simulation process is high then the optimization has gone to practice and directs the simulation process. The response surface method is used as one of the approaches of simulation optimization. Furthermore, data envelopment analysis is used to consider several response surfaces as efficiency response surface. Then this efficiency response surface is solved by Cuckoo algorithms. The main advantage of DRC model is to make one efficiency response surface function instate of multi surface function for every output and also using the advantages of Cuckoo algorithms. In order to demonstrate the effectiveness of the proposed approach, the branches of Refah bank in Mashhad is analyzed and the results are presented.

Optimization of Chassis Frame by Using D-Optimal Response Surface Model (D-Optimal 반응표면모델에 의한 섀시 프레임 최적설치)

  • Lee, Gwang-Gi;Gu, Ja-Gyeom;Lee, Tae-Hui
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.24 no.4
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    • pp.894-900
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    • 2000
  • Optimization of chassis frame is performed according to the minimization of eleven responses representing one total frame weight, three natural frequencies and seven strength limits of chassis frame that are analyzed by using each response surface model from D-optimal design of experiments. After each response surface model is constructed form D-optimal design and random orthogonal array, the main effect and sensitivity analyses are successfully carried out by using this approximated regression model and the optimal solutions are obtained by using a nonlinear programming method. The response surface models and the optimization algorithms are used together to obtain the optimal design of chassis frame. The eleven-polynomial response surface models of the thirteen frame members (design factors) are constructed by using D-optimal Design and the multi-disciplinary design optimization is also performed by applying dual response analysis.

A Study on Response Surface Method Using the Vector Projection Technique (벡터투영법을 이용한 응답면기법에 관한 연구)

  • 김상효;나성원;김우곤
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • pp.167-174
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    • 1994
  • In this study, an improved response surface method is proposed. By using gradient projection method, the sampling points for creating response surface are evaluated at the region close to the failure surface. This points are combined with linear response surface function and Rackwitz-Fiessler algorithm. Also, a method controlling the range of selecting sampling points considering the non-linearity of the limit states is proposed to reduce the error produced by approximating the non-linear limit state to linear response surface. With the examples the result of the proposed method is found to be more accurate and efficient than the previous response surface method.

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Probabilistic determination of initial cable forces of cable-stayed bridges under dead loads

  • Cheng, Jin;Xiao, Ru-Cheng;Jiang, Jian-Jing
    • Structural Engineering and Mechanics
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    • v.17 no.2
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    • pp.267-279
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    • 2004
  • This paper presents an improved Monte Carlo simulation for the probabilistic determination of initial cable forces of cable-stayed bridges under dead loads using the response surfaces method. A response surface (i.e. a quadratic response surface without cross-terms) is used to approximate structural response. The use of the response surface eliminates the need to perform a deterministic analysis in each simulation loop. In addition, use of the response surface requires fewer simulation loops than conventional Monte Carlo simulation. Thereby, the computation time is saved significantly. The statistics (e.g. mean value, standard deviation) of the structural response are calculated through conventional Monte Carlo simulation method. By using Monte Carlo simulation, it is possible to use the existing deterministic finite element code without modifying it. Probabilistic analysis of a truss demonstrates the proposed method' efficiency and accuracy; probabilistic determination of initial cable forces of a cable-stayed bridge under dead loads verifies the method's applicability.