• 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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Evaluation of Structural Design Enhancement and Sensitivity of Automatic Ocean Salt Collector According to Design of Experiments

  • Song, Chang Yong;Lee, Dong-Jun;Lee, Jin Sun;Kim, Eun Mi;Choi, Bo-Youp
    • Journal of Ocean Engineering and Technology
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    • v.34 no.4
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    • pp.253-262
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    • 2020
  • This study provides a comparative analysis of experiments-based enhancements and sensitivity evaluations for the structural design of an automatic ocean salt collector under various load conditions. The sizing variables of the structural members were considered as design factors. The strength and weight performances were selected as output responses. The design of experiments used in the comparative study consisted of the orthogonal array design, Box-Behnken design, and central composite design. The response surface model, one of the metamodels, was applied to the approximate model generation. The design enhancement performance metrics, including numerical costs and weight minimization, according to the design of experiments, were compared from the best design case results. The central composite design method showed the most enhanced design results for the structural design of the automatic ocean salt collector.

Experimental Designs for Computer Experiments and for Industrial Experiments with Model Unknown

  • Fang, Kai-Tai
    • Journal of the Korean Statistical Society
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    • v.31 no.3
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    • pp.277-299
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    • 2002
  • Most statistical designs, such as orthogonal designs and optimal designs, are based on a specific statistical model. It is very often that the experimenter does not completely know the underlying model between the response and the factors. In computer experiments, the underlying model is known, but too complicated. In this case we can treat the model as a black box, or model to be unknown. Both cases need a space filling design. The uniform design is one of space filling designs and seeks experimental points to be uniformly scattered on the domain. The uniform design can be used for computer experiments and also for industrial experiments when the underlying model is unknown. In this paper we shall introduce the theory and method of the uniform design and related data analysis and modelling methods. Applications of the uniform design to industry and other areas are discussed.

컴퓨터 모니터 디자인 개발에서 인간공학 응용

  • 신명철
    • Proceedings of the ESK Conference
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    • pp.320-325
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    • 1997
  • It is very diffcult to applied ergonomics data & experiments in industrial design. At the industrial design process attempted toadoption a egonomics. But sometimes easyto use ergonomics data and at other times very hard to adopted a element into a design process. Industrial design of the essence is a sensual act. As ergonomics data is to the hardware, sois the design sense to the software. The harmony are important to hardware & software of design process. New products demand to new form. Therefore, designer neglect to ergonomics experiments for user. Anyway, ergonomics experiments & data endlessly applied to more things year after year. This paper show improved computer front design with graphic, knobs size & control panel tilt angle.

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Application of Design of Experiments and Numerical Analysis to Optimal Design for Injection Molding Processes of Electrical Parts (실험계획법과 수치해석을 연계한 정밀 전자부품 사출성형 공정의 최적설계)

  • Ahn, Jong-Ho;Choi, Sang-Ryun;Park, Keun
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.26 no.7
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    • pp.1348-1356
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    • 2002
  • The present work concerns the optimal design for injection molding processes by using the design of experiments (DOE) and numerical analysis. The DOE approaches is planned to be able to consider two-way interaction, and have been applied progressively for both mold design and process design. Numerical analyses have been carried out as a design of experiments for mold parameters such as runner specifications and cooling channel configurations. In order to determine optimal process parameters, experiments have been performed for various process conditions with the DOE scheduling. As a result, the quality and productivity of the product have been improved, and the proposed approach can be successfully reflected on the industrial injection molding process of precision electronics parts.

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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A Design Methodology with Orthogonal Arrays Using Experiments and Computer Simulations (실험과 컴퓨터 모사 결과를 동시에 이용하여 직교배열표로 설계하는 방법)

  • Park, Gyung-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.28 no.7
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    • pp.885-895
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    • 2004
  • Generally, automatic design is carried out with computer simulation and the simulation models are established by investigating the correlations between the simulation and real experiments. Therefore, the experiment results are utilized as complimentary data although they are considered to be precise. Orthogonal arrays have been adopted for discrete design. A method is proposed to directly exploit the experiment results in the design process with orthogonal arrays. Experiments are allocated to some rows of an orthogonal array and computer simulations are allocated to the others. A rule for the allocation is found to keep the orthogonality. Error analysis of the design results is performed. Mathematical examples are made to verify the validity of the proposed method. Error models are defined with the examples and the design solutions from the examples are discussed.

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.

A Study on the Optimal Grinding Condition of Ceramics using the Design of Experiments (실험 계획법을 이용한 세라믹 재료의 최적 연삭 조건에 관한 연구)

  • Jeong, Eul-Seop;Kim, Seong-Cheong;So, Ui-Yeol;Lee, Geun-Sang
    • Journal of the Korean Society for Precision Engineering
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    • v.19 no.8
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    • pp.141-146
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    • 2002
  • This paper has studied to obtain the grinding characteristics and optimal grinding conditions of ceramic materials in the grinding with diamond wheel by design of experiments. The load on wheel by varying the feed rate was related with the surface roughness due to the minute destruction phenomenon of grains for the $Si_3\;N_4\;and\;ZrO_2$. The depth of cut is related with the surface roughness because the grinding is carried out by grain shedding process due to the brittle fracture phenomenon for the $A1_2\;O_3$. The major factors affecting the surface roughness and the optimum grinding conditions were obtained with minimum experiments using design of experiments.

Suspension Parameter Design Using a Desingn of Experiments (실험계획법을 이용한 현가장치의 요소설계)

  • 김상중;박찬종;박태원
    • Transactions of the Korean Society of Automotive Engineers
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    • v.4 no.1
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    • pp.16-27
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    • 1996
  • Using computer in design is a trend in recent years. A good suspension model is depend on the carefully prepared data like joint connection points or spring stiffness, etc. Once a good computer model is obtained, a parametric study for spciffic suspension design factor, like a toe angle, can be done to obtain sensitivity information. Using this information, several important design parameters for a specific design factor can be identified. Once a design of experiments is done using computer models, the results can be used to approximate a function which can best represent the experimentation. An optimum solution of this function can be used to find an optimum design of a suspension system for a specific suspension design factor. Same method is again applied to other design factors iteratively until a good suspension system design is obtained.

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