• Title/Summary/Keyword: ANOVA- test(Analysis of variance)

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Pridiction of chip breakability by an orthogonal array method (직교배열법에 의한 칩절단특성 예측)

  • 이영문;양승한;권오진
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2001.04a
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    • pp.1008-1011
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    • 2001
  • The purpose of this paper is to evaluate the chip breakability during turning using the experimental equation, which is developed by an orthogonal array method. The chip breaking index(CB), non-dimensional parameter is used in the evaluation of chip breakability. The analysis of variance(ANOVA)-test has been used to check the significance of cutting parameters. And using the result of ANOVA-test, the experimental equation of chip breakability, which consists of significant cutting parameters, has been developed.

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Pooling Variance Tests Using Expected Mean Square in Split-Plot Designs (분할법에서 EMS알고리즘을 이용한 풀링분산검정)

  • Choi, Sung-Woon
    • Journal of the Korea Safety Management & Science
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    • v.10 no.3
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    • pp.245-251
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    • 2008
  • The research proposes three ANOVA(Analysis of Variance) tests using expected mean square(EMS) algorithms in various split-plot designs. The variance tests consist of Never-Pool test, Sometimes-Pool test and Always-Pool test. This paper also presents two EMS algorithms such as standard method and easy method. These algorithms are useful to make a decision rule for pooling. Numerical examples are illustrated for various split-plot designs such as split-plot designs, split-split-plot designs, repetition split-plot designs, and nested designs. Pragmatically, the results are summarized and compared with popular ANOVA spreadsheets and data model equations.

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

  • 배병중;박태준;양승한;이영문;김희술
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2000.11a
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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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Process Optimization for Co-based Self-flux Alloy Coating by Taguchi Method (다구찌 기법에 의한 코발트기 자융성합금 용사코팅의 최적공정 설계)

  • Lee, Jae-Hong;Kim, Yeong-Sik
    • Journal of Power System Engineering
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    • v.17 no.6
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    • pp.108-114
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    • 2013
  • This paper describes process optimization for thermal-sprayed Co-based self-flux alloy coating by Taguchi method. Co-based self-flux alloy coatings were fabricated according to $L_9(3^4)$ orthogonal array using flame spray process. Hardness test and wear test were performed, the results were analyzed by analysis of variance(ANOVA) considering a multi response signal to noise ratio(MRSN). From the results of ANOVA, the optimal combination of the flame spray parameters on Co-based self-flux alloy coating could be predicted. The calculated hardness and wear rate of the coatings by ANOVA were found to be close to that of confirmation experimental result.

Application of functional ANOVA and functional MANOVA (단변량 및 다변량 함수 데이터에 대한 분산분석의 활용)

  • Kim, Mijeong
    • The Korean Journal of Applied Statistics
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    • v.35 no.5
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    • pp.579-591
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    • 2022
  • Functional data is collected in various fields. It is often necessary to test whether there are differences among groups of functional data. In this case, it is not appropriate to explain using the point-wise ANOVA method, and we should present not the point-wise result but the integrated result. Various studies on functional data analysis of variance have been proposed, and recently implemented those methods in the package fdANOVA of R. In this paper, I first explain ANOVA and multivariate ANOVA, then I will introduce various methods of analysis of variance for univariate and multivariate functional data recently proposed. I also describe how to use the R package fdANOVA. This package is used to test equality of weekly temperatures in Seoul and Busan through univariate functional data ANOVA, and to test equality of multivariate functional data corresponding to handwritten images using multivariate function data ANOVA.

Unbalanced ANOVA for Testing Shape Variability in Statistical Shape Analysis

  • Kim, Jong-Geon;Choi, Yong-Seok;Lee, Nae-Young
    • The Korean Journal of Applied Statistics
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    • v.23 no.2
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    • pp.317-323
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    • 2010
  • Measures are very useful tools for comparing the shape variability in statistical shape analysis. For examples, the Procrustes statistic(PS) is isolated measure, and the mean Procrustes statistic(MPS) and the root mean square measure(RMS) are overall measures. But these measures are very subjective, complicated and moreover these measures are not statistical for comparing the shape variability. Therefore we need to study some tests. It is well known that the Hotelling's $T^2$ test is used for testing shape variability of two independent samples. And for testing shape variabilities of several independent samples, instead of the Hotelling's $T^2$ test, one way analysis of variance(ANOVA) can be applied. In fact, this one way ANOVA is based on the balanced samples of equal size which is called as BANOVA. However, If we have unbalanced samples with unequal size, we can not use BANOVA. Therefore we propose the unbalanced analysis of variance(UNBANOVA) for testing shape variabilities of several independent samples of unequal size.

Process Optimization of Thermal-sprayed STS316 Coating (STS316 용사코팅의 최적 공정 설계)

  • Kim, Kyun-Tak;Kim, Yeong-Sik
    • Journal of Ocean Engineering and Technology
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    • v.24 no.1
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    • pp.161-165
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    • 2010
  • In the present study, process optimization for thermal-sprayed STS316 coating has been performed using $L_9(3^4)$ orthogonal array and analysis of variance (ANOVA). STS316 coatings were fabricated by flame spray process on steel substrate, and the hardness test and microstructure observation of the coatings were studied. The results of hardness test were analyzed by ANOVA. The ANOVA results showed that the spray distance had the greatest effect on hardness of the coating, on the other hands, the effects of oxygen gas flow and spray distance were ignorable. From these results, the optimal combination of the flame spray parameters could be derived, and confirmation experiment was carried out to verify these derived results. The calculated hardness of the coatings by ANOVA was found to approximately close to that of confirmation experimental result. Thus, it was considered that design of experiments using orthogonal array and ANOVA was effective for process optimization of thermal-sprayed STS316 coating.

Process Optimization for Thermal-sprayed Ni-based Hard Coating by Design of Experiments (실험계획법에 의한 니켈기 경질 용사코팅의 최적 공정 설계)

  • Kim, K.T.;Kim, Y.S.
    • Journal of Power System Engineering
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    • v.13 no.5
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    • pp.89-94
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    • 2009
  • In this work, the optimal process has been designed by $L_9(3^4)$ orthogonal array and analysis of variance(ANOVA) for thermal-sprayed Ni-based hard coating. Ni-based hard coatings were fabricated by flame spray process on steel substrate. Then, the hardness test and observation of microstructure of the coatings were performed. The results of hardness test were analyzed by ANOVA. The ANOVA results demonstrated that the acetylene gas flow had the greatest effect on hardness of the coatings. The oxygen gas flow was found to have a neglecting effect. From these results, the optimal combination of the flame spray parameters could be predicted. The calculated hardness of the coatings by ANOVA was found to lie close to that of confirmation experimental result. Thus, it was considered that design of experiments design using orthogonal array and ANOVA was useful to determine optimal process of thermal-sprayed Ni-based hard coating.

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Evaluating the Effect of Specimen Thickness on Fatigue Crack Growth in AZ31 Alloy Using ANOVA (분산분석법을 이용한 AZ31 합금의 피로균열성장에 미치는 시편두께 효과 평가)

  • Choi, Seon Soon
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.19 no.6
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    • pp.9-16
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    • 2020
  • This study aims to assess the effects of specimen thickness (ST) on fatigue crack growth in the early stages of crack propagation and near failure in magnesium alloys. The analysis of variance (ANOVA) method was adopted because fatigue crack propagation in magnesium alloys exhibits statistical behavior. The equality of variance test and residual diagnostics were performed on the grown cracks to confirm the validity of ANOVA by verifying the normal distribution and mutual independence of the residuals and their homoscedasticity. ANOVA confirmed that ST heavily impacts crack growth; i.e., when ST is smaller, cracks grow faster in the early crack propagation stage and break more quickly before the formation of larger cracks. We found that ST significantly affects fatigue crack growth in the early crack propagation stage and near the failure stage in magnesium alloys. The regression model was also used to predict crack formation near the failure stage.

Quasi-static Analysis of Vehicle Seatbelt Using Analysis of Variance and Improvement of Tensile Test Correlation (분산 분석을 이용한 자동차 안전벨트 준정적 해석과 인장시험 상관성 개선)

  • Lee, Kwangseop;Eo, Youngwoo;Kim, Samsung;Kim, Dooyong;Song, Taeckrim;Lee, Kyeongsang
    • Transactions of the Korean Society of Automotive Engineers
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    • v.24 no.3
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    • pp.273-278
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    • 2016
  • This study makes a relative comparison of the results of tensile test and quasi-static analysis using AGL(Adjuster Guide Loop) model that plays a role in adjusting the height of shoulder belt, of the components of the vehicle seatbelt system and attempts to propose a method of reducing the error rate of the quasi-static analysis technique effectively. This study selects two major factors affecting the result of an analysis, draws the result of analysis through the method of experimental design, one of the statistical techniques and understands the contribution rate of the major factors affecting the result of the analysis through ANOVA(Analysis of Variance).