• 제목/요약/키워드: fractional factorial design method

검색결과 47건 처리시간 0.022초

$p^{n-m}$ fractional Factorial Design Excluded SOme Debarred Combinations

  • Choi, Byoung-Chul;Kim, Hyuk-Joo
    • Communications for Statistical Applications and Methods
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    • 제7권3호
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    • pp.759-766
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    • 2000
  • In order to design fractional factorial experiments which include some debarred combinations, we should select defining contrasts so that those combinations are to be excluded. Choi(1999) presented a method of selectign defining contrasts to construct orthogonal 3-level fractional factorial experiments which exclude some debarred combinations. In this paper, we extend Choi's method to general p-level fractional factorial experiments to select defining contrasts which cold exclude some debarred combinations.

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다구찌 방법과 실험계획법을 이용한 소음기의 설계 방법 (Design of Muffler using Taguchi Method and Experimental Design)

  • 오재응;차경준;이규태;진정언
    • 한국자동차공학회논문집
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    • 제7권5호
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    • pp.121-129
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    • 1999
  • Recently, the regulations from the govemment and the concems of the people give rise to the interest in exhaust noise of passenger car as much as other vehicles. The exact analysis of various mufflers is needed to reduce the level of exhaust noise. In this paper, we propose a design to improve the mufflers capacity by reducing noise of exhaust system combining Taguchi method and fractional factorial design. In order to measure the performance of a muffler, the performance prediction software which is developed by the Dept. of Automotive Engineering at Hanyang University is used. From the current muffler system we select control factors such as lenght and radius of each component that are thought to be effective on capacity of muffler. Factors are arranged using L18, L27 table of orthogonal array and the fractional factorial design for analysis. We find some significant interaction effects using 1/3 fractional factorial design and accomplish the reduction of noise from the muffler.

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3n-p Fractional Factorial Design Excluded Some Debarred Combinations

  • Park, Byoung -Chul
    • Communications for Statistical Applications and Methods
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    • 제6권3호
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    • pp.695-706
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    • 1999
  • When fractional factorial experiments contain some infeasible treatment combinations called debarred combinations we should construct experimental designs so that those debarred combinations are to be excluded by selecting defining contrasts appropriately. By applying Franklin(1995)'s procedure for selecting defining contrasts to Cheng and Li(1993)'s method this paper presents a method of selecting defining contrasts to construct orthogonal 3-level fractional factorial experiments which exclude some debarred combinations.

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Noise Reduction of Muffler by Optimal Design

  • Oh, Jae-Eung;Cha, Kyung-Joon
    • Journal of Mechanical Science and Technology
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    • 제14권9호
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    • pp.947-955
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    • 2000
  • This paper proposes an optimal design scheme to improve the muffler's capacity of noise reduction of the exhaust system by combining the Taguchi method and a fractional factorial design. As a measuring tool for the performance of a muffler, the performance prediction software which is developed by Oh, Lee and Lee (1996) is used. In the first stage of a design, the length and radius of each component of the current muffler system are selected as control factors. Then, the $L_{18}$ table of orthogonal arrays is adopted to extract the effective main factors. In the second stage, the fractional factorial design is adopted to take interactions into consideration, which the $L_{18}$ table of orthogonal arrays can not consider. For an optimal design, the $L_{27}$ table of orthogonal arrays with main and interaction effects is proposed and the noise factors such as temperature, background noise and humidity are analyzed for more efficient design simultaneously.

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실험불가능한 처리조합이 배제되는 $3^{n-p}$ 일부실시법 ($3^{n-p}$ Fractional Factorial Desig Excluded A Debarred Combination)

  • 최병철;최승현
    • 응용통계연구
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    • 제11권2호
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    • pp.303-315
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    • 1998
  • 요인실험에서 어떤 처리조합은 조작상 또는 경제적인 이유로 실험할 수 없는 경우가 있다. 이러한 실험불가능한 처리조합을 포함하고 있는 일부실시법은 불균형적인 처리조합을 구성하게 되어 어떤 요인효과에 대해 추론할 수 없게 된다. 본 논문은 실험불가능한 처리조합을 포함하지 않는 3$^{n-p}$ 일부실시법을 실행하기 위한 정의 대비의 선택 방법을 논한다한다

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배열을 이용한 효과적인 일부실시법의 설계 및 분석방법에 관한 연구 (A Study on the Construction and Analysis of Fractional Designs by Using Arrays for Factorial Experiments)

  • 김상익
    • 품질경영학회지
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    • 제40권1호
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    • pp.15-24
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    • 2012
  • For the construction of fractional factorial designs, the various arrays can be widely used. In this paper we review the statistical properties of fractional designs constructed by two arrays such as orthogonal array and partially balanced array, and develop a quick and easy method for analyzing unreplicated saturated designs. The proposed method can be characterized that we control the error rate by experiment-wise way and exploit the multivariate Student $t$-distribution. Especially the proposed method can be used efficiently together with some exploratory analysis methods, such as half normal probability plot method.

직교배열법에 의한 선삭가공시 표면거칠기 평가 (Surface roughness evaluation in turning by an orthogonal array method)

  • 배병중;박태준;양승한;이영문;김희술
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2000년도 추계학술대회 논문집
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    • pp.862-865
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    • 2000
  • The object of this paper is to evaluate the surface roughness using the experimental equation of surface roughness, which is developed in turning by an orthogonal array method. $L_9{3^4}$ orthogonal array method, one of fractional factorial design has been used to study effects of main cutting parameters such as cutting speed, feed rate and depth of cut, on the surface roughness. And the analysis of variance (ANOVA)-test has been used to check the significance of cutting parameters. Using the result of ANOVA-test, the experimental equation of surface roughness, which consists of only significant cutting parameter - feed rate, has been developed. The coefficient of determination of this equation is 0.962.

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일반화 선형모형의 디자인 행렬을 이용한 품질 실험 설계 (Design of Experiment Using Design Matrix in Terms of Generalized Linear Model)

  • 최성운
    • 대한안전경영과학회:학술대회논문집
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    • 대한안전경영과학회 2009년도 춘계학술대회
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    • pp.423-427
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    • 2009
  • This study proposes the generation mechanism of various design matrix using generalized linear model for design of experiment. Design generation method of GLM analysis, factorial design(FD) with center points, ANOVA design with lack-of-fit test, and response surface design are introduced. In central composite(CC) design, orthogonal blocking and fractional factorial design(FFD) are presented. We compare the design of Box-Benhken(BB) and face-centred central compsite design.

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RESIDUALS IN MINIMAL RESOLUTION IV DESIGNS

  • Liau, Pen-Hwang
    • Journal of the Korean Statistical Society
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    • 제32권3호
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    • pp.235-244
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    • 2003
  • In unreplicated factorial or fractional factorial experiments, the presence of one or more outliers can seriously affect the analysis of variance. Using the normal plot of t residuals to identify outliers in factorial or fractional factorial is an easy method to find these dubious points. In some cases, the t residuals form the identical pairs. One can not tell from the plot which is doubtful. This phenomenon occurs for all minimal designs of resolution IV, which fits the model containing all main effects and some two-factor interactions, whether it is orthogonal or not. In these kinds of models, when we drop one point or two points (not foldover pair) from the fraction, the phenomenon of identical pairs of t residuals may still occur. In this paper, the theoretical background of the phenomenon and its sequences will be investigated in detail.

Classification Rule for Optimal Blocking for Nonregular Factorial Designs

  • Park, Dong-Kwon;Kim, Hyoung-Soon;Kang, Hee-Kyoung
    • Communications for Statistical Applications and Methods
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    • 제14권3호
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    • pp.483-495
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    • 2007
  • In a general fractional factorial design, the n-levels of a factor are coded by the $n^{th}$ roots of the unity. Pistone and Rogantin (2007) gave a full generalization to mixed-level designs of the theory of the polynomial indicator function using this device. This article discusses the optimal blocking scheme for nonregular designs. According to hierarchical principle, the minimum aberration (MA) has been used as an important criterion for selecting blocked regular fractional factorial designs. MA criterion is mainly based on the defining contrast groups, which only exist for regular designs but not for nonregular designs. Recently, Cheng et al. (2004) adapted the generalized (G)-MA criterion discussed by Tang and Deng (1999) in studying $2^p$ optimal blocking scheme for nonregular factorial designs. The approach is based on the method of replacement by assigning $2^p$ blocks the distinct level combinations in the column with different blocks. However, when blocking level is not a power of two, we have no clue yet in any sense. As an example, suppose we experiment during 3 days for 12-run Plackett-Burman design. How can we arrange the 12-runs into the three blocks? To solve the problem, we apply G-MA criterion to nonregular mixed-level blocked scheme via the mixed-level indicator function and give an answer for the question.