• Title/Summary/Keyword: 실험계획법

Search Result 1,328, Processing Time 0.031 seconds

An Improved Stochastic Algorithm Using Kriging for Practical Optimal Designs (크리깅을 이용한 개선된 확률론적 최적화 알고리즘)

  • 임종빈;박정선;노영희
    • Journal of the Korean Society for Aeronautical & Space Sciences
    • /
    • v.34 no.9
    • /
    • pp.33-44
    • /
    • 2006
  • As many scientific phenomena are now investigated using complex computer models, the effective use of Kriging on physical problems has been expanded to provide global approximations for optimization problems. This paper is focused on the two types of strategies to improve efficiency and accuracy of approximate optimization models using Kriging. These methods are performed by the stochastic process, stochastic-localization method(SLM), as the criterion to move the local domains and the design of experiments(DOE), the classical design and space-filling design. The proposed methodology is applied to the designs of 3-bar truss, Sandgren's pressure vessel, and honeycomb upper platform of a satellite structure.

Composite Design Criteria : Model and Variance (복합실험기준의 설정: 모형과 분산구조)

  • 김영일
    • The Korean Journal of Applied Statistics
    • /
    • v.13 no.2
    • /
    • pp.393-405
    • /
    • 2000
  • Box and Draper( 19(5) listed some properties of a design that should be considered in design selection. But it is impossible that one design criterion from optimal experimental design theory reflects many potential objectives of an experiment, because the theory was originally based on the underlying model and its strict assumption about the error structure. Therefore, when it is neces::;ary to implement multi-objective experimental design. it is common practice to balance out the several optimal design criteria so that each design criterion involved benefits in terms of its relative "high" efficiency. In this study, we proposed several composite design criteria taking the case of heteroscedastic model. WVhen the heteroscedasticity is present in the model. the well known equivalence theorem between 1)- and C-optimality no longer exists and furthermore their design characteristics are sometimes drastically different. We introduced three different design criteria for this purpose: constrained design, combined design, and minimax design criteria. While the first two methods do reflect the prior belief of experimenter, the last one does not take it into account. which is sometimes desirable. Also we extended this method to the case when there are uncertainties concerning the error structure in the model. A simple algorithm and concluslOn follow.On follow.

  • PDF

$ fractional factorial designs of resolution V and taguchi method

  • 김상익
    • The Korean Journal of Applied Statistics
    • /
    • v.5 no.1
    • /
    • pp.19-28
    • /
    • 1992
  • In this paper, minimal balanced $2^t$ fractional factorial designs which permit the estimation of main effects and 2-factor interactions are developed by using a partially balanced array. Such designs are characterized by a minimum number of runs and some balancedness property of the variance-covariance matrix of the estimates. In addition to describing the designs, optimality criteria are discussed and the trace-optimal designs are presented. The proposed designs are especially useful in Taguchi method, where we need to investigate up to 2-factor interactions of the control factors.

  • PDF

Development of Optimization Algorithm for Unconstrained Problems Using the Sequential Design of Experiments and Artificial Neural Network (순차적 실험계획법과 인공신경망을 이용한 제한조건이 없는 문제의 최적화 알고리즘 개발)

  • Lee, Jung-Hwan;Suh, Myung-Won
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.32 no.3
    • /
    • pp.258-266
    • /
    • 2008
  • The conventional approximate optimization method, which uses the statistical design of experiments(DOE) and response surface method(RSM), can derive an approximated optimum results through the iterative process by a trial and error. The quality of results depends seriously on the factors and levels assigned by a designer. The purpose of this study is to propose a new technique, which is called a sequential design of experiments(SDOE), to reduce a trial and error procedure and to find an appropriate condition for using artificial neural network(ANN) systematically. An appropriate condition is determined from the iterative process based on the analysis of means. With this new technique and ANN, it is possible to find an optimum design accurately and efficiently. The suggested algorithm has been applied to various mathematical examples and a structural problem.

The Porosity Change of Glass Frit with Sintering Condition (소결조건에 따른 Glass Frit의 기공량 변화)

  • Yang, Jin
    • Korean Journal of Materials Research
    • /
    • v.8 no.11
    • /
    • pp.1005-1010
    • /
    • 1998
  • 실험계획법을 이용하여 유리분말의 소결시 그 기공량에 영향을 미치는 각종 소결조건의 영향을 정량적으로 조사하였다. 본 실험범위내에서 결합제 유리의 총기공량, 개기공량 그미고 폐기공량은 모두 소결온도에 의해 가장 큰 영향을 받고 그 다음으로 소결온도에서의 유지시간에 의해 영향을 받으며 승온속도의 경우 그 영향이 상대적으로 미미함을 확인할 수 있었다. 이러한 결과들로부터 실제공정에 있어 승온속도보다는 다른 소결인자, 특히 소결온도를 조절하는 것이 결합제 유리의 기공량 조절에 가장 중요하리라 판단되며 실험계획법을 이용함으로써 보다 정확한 공전조건을 모색할 수 있었다.

  • PDF

신뢰성을 고려한 열유체 시스템의 최적화 설계

  • 오정열;허용정
    • Proceedings of the Korean Society Of Semiconductor Equipment Technology
    • /
    • 2005.09a
    • /
    • pp.178-182
    • /
    • 2005
  • 품질 관리의 목표는 최종제품의 품질 보증에 있다. 이러한 목표를 달성하기 위해서는 품질 특성이 명확해야 하며, 동시에 품질 특성치에 영향을 주는 공정의 여러 변동 요인을 분명히 해야 한다. 실험계획법(Design of Experiments)은 특성에 영향을 미치는 여러 인자를 선정하며, 또한 이들의 관계를 알아보기 위한 실험을 실시하여 제품의 최적 제조조건을 경제적으로 찾아내는 기법이다. 본 연구에서는 실험계획법을 사용하여 유량을 최적화하는 요인을 선정, 얻어진 데이터를 통계적 방법으로 분석하여 최적의 조건을 나타내었다.

  • PDF

Development of Optimization Algorithm Using Sequential Design of Experiments and Micro-Genetic Algorithm (순차적 실험계획법과 마이크로 유전알고리즘을 이용한 최적화 알고리즘 개발)

  • Lee, Jung Hwan;Suh, Myung Won
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.38 no.5
    • /
    • pp.489-495
    • /
    • 2014
  • A micro-genetic algorithm (MGA) is one of the improved forms of a genetic algorithm. It is used to reduce the number of iterations and the computing resources required by using small populations. The efficiency of MGAs has been proved through many problems, especially problems with 3-5 design variables. This study proposes an optimization algorithm based on the sequential design of experiments (SDOE) and an MGA. In a previous study, the authors used the SDOE technique to reduce trial-and-error in the conventional approximate optimization method by using the statistical design of experiments (DOE) and response surface method (RSM) systematically. The proposed algorithm has been applied to various mathematical examples and a structural problem.

Optimal Design of a Mini-Loader Based on the Design of Experiments (실험계획법을 이용한 미니로더의 최적설계)

  • Kwon, Ki-Beom;Shin, Dea-Young
    • Transactions of the Korean Society of Mechanical Engineers A
    • /
    • v.35 no.6
    • /
    • pp.693-699
    • /
    • 2011
  • In this study, a hydraulic system of a mini-loader is modeled, and the model is validated by comparing the simulation results to the experimental results. A load force acting on the structure of the mini-loader is obtained from the simulation of the hydraulic system, and the structural analysis via finite element method is performed using the obtained load force to evaluate the structural safety of the loader. For the mainframe that requires additional strengthening according to the structural analysis, the optimum design parameters are proposed using the design of experiments to improve strength without additional mass.

Optimization of MOF-801 Synthesis Using Sequential Design of Experiments (순차적 실험계획법을 이용한 MOF-801 합성공정 최적화)

  • Lee, Min Hyung;Yoo, Kye Sang
    • Applied Chemistry for Engineering
    • /
    • v.32 no.6
    • /
    • pp.621-626
    • /
    • 2021
  • A sequential design of experiments was used to optimize MOF-801 synthesis process. For the initial screening, a general 2k factorial design was selected followed by the central composition design, one of the response surface methods. A 23 factorial design based on the molar ratio of fumaric acid, dimethylformamide (DMF), and formic acid was performed to select the more suitable response variable for the design of experimental method among the crystallinity and BET specific surface area of MOF-801. After performing 8 synthesis experiments designed by MINITAB 19 software, the characteristic analysis was performed using XRD analysis and nitrogen adsorption method. The crystallinity with R2 = 0.999 was found to be more suitable for the experimental method than that of BET specific surface area. Based on analysis of variance (ANOVA), it was confirmed that the molar ratio of fumaric acid and formic acid was a major factor in determining the crystallinity of MOF-801. Through the response optimization and contour plot of two factors, the optimal molar ratio of ZrOCl2·8H2O : fumaric acid : DMF : formic acid was 1 : 1 : 39 : 35. In order to optimize the synthesis process, the central composition design on synthesis time and temperature was performed under the identical molar ratio of precursors. The results derived through the designed 9 synthesis experiments were calculated using the quadratic model equation. Thus, the maximum crystallinity of MOF-801 predicted under the synthesis time and temperature of 7.8 h and 123 ℃, respectively.