• Korean Journal of Food Science and Technology
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• v.24 no.1
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• pp.74-81
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• 1992

To develop the beverage from Schizandra chinensis Baillon, extraction condition was optimized, using the fractional factorial design with 3 variables and 3 levels, by a RSM computer program. The optimum extraction time, extraction temperature and alcohol concentration levels were 3 hrs, $80{\sim}85^{\circ}C$ and 0%(water) for a desired yield, color and non-volatile organic acid. And to obtain the optimum recipe, amounts of extract, sugar and citric acid were optimized, using the fractional factorial design with 3 variables and 3 levels, by a RSM program. The optimum extract, sugar and citric acid levels were 4%, 9.6%n and 0.06%, respectively, for a disired flavor and overall acceptance.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.4
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• pp.352-365
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• 2001

Two-level factorial designs are popular in industry due to their simplicity, efficiency, graphical interpretation, and flexibility in sequential experimentation. However, experimenters are often frustrated when they have factors with more than two levels. There have been some works on design of experiments with two- and four-level factors, which mostly deal with qualitative four-level factors. This paper discusses differences between qualitative and quantitative four-level factors. Optimal designs are provided for some designs with four-level quantitative and two-level factors.

• Journal of Korean Society for Quality Management
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• v.32 no.3
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• pp.234-243
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• 2004

In this paper, we study the optimality of 2-level resolution V minimal fractional factorial designs which can be constructed by using a partially balanced array. Moreover the relative efficiencies of such designs are compared in the sense of three optimality criteria such as determinant(D)-optimality, trace(A)-optimality, and eigenvalue(E) -optimality criterion.

• Journal of the Korean Statistical Society
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• v.32 no.3
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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.

• Proceedings of the Safety Management and Science Conference
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• 2009.04a
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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.

• Journal of Korean Society for Quality Management
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• v.40 no.1
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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.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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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.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.4
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• pp.430-435
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• 2009

The cooling stage greatly affects the product quality in the injection molding process. The cooling system that minimizes temperature variance in the product surface will improve the quality and the productivity of products. The cooling circuit optimization problem that was once solved by a response surface method with 4 design variables. It took too much time for the optimization as an industrial design tool. It is desirable to reduce the optimization time. Therefore, we tried the back-propagation algorithm of artificial neural network(BPN) to find an optimum solution in the cooling circuit design in this research. We tried various ways to select training points for the BPN. The same optimum solution was obtained by applying the BPN with reduced number of training points by the fractional factorial design.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.05a
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• pp.357-360
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• 2009

The cooling stage greatly affects the product quality in the injection molding process. The cooling system that minimizes temperature variance in the product surface will improve the quality and the productivity of products. In this research, we tried the back-propagation algorithm of artificial neural network to find an optimum solution in the cooling system design of injection mold. The cooling system optimization problem that was once solved by a response surface method with 4 design variables was solved by applying the back-propagation algorithm, resulting in a solution with a sufficient accuracy. Furthermore the number of training points was much reduced by applying the fractional factorial design without losing solution accuracy.

• Journal of the Korea Safety Management & Science
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• v.7 no.5
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• pp.69-84
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• 2005

This paper proposes statistically designed experiments which provide a proactive means to implement safety and environmental applications. Minimal experimental designs such as fractional factorial design, Plackett-Burman design, Box-Behnken design are economical and can be achieved tremendous savings with relatively few experiments. These experimental designs and analysis methods are illustrated with cases.