• Title/Summary/Keyword: Design of experiments

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Optimal Design for Injection Molding Processes using Design of Experiments and Finite Element Analysis (실험계획법과 유한요소해석을 연계한 사출성형 공정의 최적설계)

  • Park K.;Ahn J. H.;Choi S.R.
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • pp.150-153
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    • 2001
  • The present work concerns optimal design for the injection molding process of a deflection yoke (coil separator). The optimal design for the injection molding process is developed using design of experiments and finite element analysis. Two design of experiments approaches are applied such as: the design of experiment for mold design and the design the experiments for determination of process parameters. Finite element analyses have been carried out as a design of experiments for mold design: runner system and cooling channel. In order to determine optimal process experiments have been performed for various process conditions with the design of experiments scheduling.

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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
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    • v.32 no.3
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    • pp.258-266
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    • 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.

A study on configuration of acoustic package for towed array sonar using design of experiments (실험계획법을 이용한 예인 음탐기용 음향패키지 형상 연구)

  • Lee, JungHyun;Shin, Jeungho;Kwon, Oh-Cho;Kim, Gunchil
    • The Journal of the Acoustical Society of Korea
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    • v.38 no.2
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    • pp.200-206
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    • 2019
  • In this paper, the characteristics of receiving voltage sensitivity about acoustic package in towed array sonar is analyzed through the numerical simulation and design of experiments. Simulation results show that the variation of receiving voltage sensitivity is caused by the structural resonance mode shape on baseline acoustic package. The effect of design parameters of the acoustic package are analyzed through the design of experiments to reduce the deviation of receiving voltage sensitivity. A change of hydrophone shield can thickness (t) is the greatest effect on the deviation of receiving voltage sensitivity. As a result of water tank test, the acoustic package derived from the design of experiments has reduced deviation of receiving voltage sensitivity.

Optimum Design based on Sequential Design of Experiments and Artificial Neural Network for Heat Resistant Characteristics Enhancement in Front Pillar Trim (프런트 필라 트림의 내열특성 향상을 위한 순차적 실험계획법과 인공신경망 기반의 최적설계)

  • Lee, Jung Hwan;Suh, Myung Won
    • Journal of the Korean Society for Precision Engineering
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    • v.30 no.10
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    • pp.1079-1086
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    • 2013
  • Optimal mount position of a front pillar trim considering heat resistant characteristics can be determined by two methods. One is conventional approximate optimization method which uses the statistical design of experiments (DOE) and response surface method (RSM). Generally, approximated optimum results are obtained 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 other is a methodology derived from previous work by the authors, which is called 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.

An Optimization Algorithm Using Kriging (크리킹을 이용한 최적화 알고리즘)

  • Park, Jung-Sun;Ro, Young-Hee;Im, Jong-Bin
    • Journal of the Korean Society for Aviation and Aeronautics
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    • v.14 no.1
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    • pp.36-42
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    • 2006
  • Kriging has been effectively used to approximate for optimization. This study has been devised to improve efficiency and accuracy of approximate optimal design using Kriging. The design of experiments (DOE), the classical design and space-filling design, are used to provide maximum information using minimum number of design of experiments. The proposed methodology is applied to the designs of 3-bar truss and Sandgren's pressure vessel.

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Geometric Error Analysis of Surface Grinding by Design of Experiments (실험계획법을 이용한 연삭가공물의 형상오차 분석)

  • 지용주;곽재섭;하만경
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.13 no.4
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    • pp.1-8
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    • 2004
  • Various controllable parameters of an experiment have influence on grinding process. In order to get good products with a high quality, these parameters should be considered whether each parameter has relations to the quality. This paper describes the use of the design of experiments to minimize geometric error in surface grinding. Controllable parameters for the design of experiments were selected as spindle speed, table speed, depth of cut and grain size. From the experimental results, a degree of influence between these parameters and the geometric error was evaluated. An optimal set of grinding conditions was obtained by means of analysis of variance(ANOVA).