• 품질경영학회지
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• 제29권1호
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• pp.24-40
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• 2001

Response surface designs can be classified, according to the shape of the experimental region, into spherical designs and cuboidal designs. Among the central composite design(CCD)s and the Box-Behnken design(BBD)s that are popular in practice, when the number of factors is k, spherical designs are tile CCDs with the axial value being $\sqrt{\textit{k}}$ and the BBDs, and cuboidal designs are the CCDs with the axial value being 1. With the CCDs having $\sqrt{\textit{k}}$ as the axial value, the radius of the experimental region varies with number of factors, but these designs are the 5-level designs. With the BBDs that are 3-level designs, the radius of the experimental region does not vary with the number of factors. In this article, we propose tile 3-level spherical designs which are constructed so that tile radius of the experimental region varies with the number of factors.

• 응용통계연구
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• 제24권5호
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• pp.893-904
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• 2011

실험계획법의 강의내용은 크게 두 개의 파트인 실험계획과 모형분석으로 대별되는데 시각화 작업은 주로 모형분석 중심으로 이루어져 왔다. 실험계획법의 강의내용에 대한 시각화 작업의 일환으로 우리는 실험계획의 시각화를 라틴 방격법의 시각화, 초포화계획법의 시각화, 불완비블럭계획법의 시각화로 나누어 고려하여 볼 수 있다. 실험계획을 시각화하는 작업을 위하여 우리는 계획그림을 제안 할 수 있고 기존의 산점도나 산점도행렬을 사용할 수 있다. 이러한 실험계획의 시각화를 통하여 우리는 이론 중심의 실험계획법 강의에 그림들을 삽입함으로써 실험계획법 수업에서의 시너지효과를 얻을 수 있다.

• 산업공학
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• 제23권2호
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• pp.118-125
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• 2010

The determination of a regression model is important in using statistical designs of experiments. Generally, the exact regression model is not known, and experimenters suppose that a certain model form will be fit. Then an experimental design suitable for that predetermined model form is selected and the experiment is conducted. However, the initially chosen regression model may not be correct, and this can result in undesirable statistical properties. We develop model-robust experimental designs that have stable prediction variance for a family of candidate regression models over a cuboidal region by using genetic algorithms and the desirability function method. We then compare the stability of prediction variance of model-robust experimental designs with those of the 3-level face centered cube. These model-robust experimental designs have moderately high G-efficiencies for all candidate models that the experimenter may potentially wish to fit, and outperform the cuboidal design for the second-order model. The G-efficiencies are provided for the model-robust experimental designs and the face centered cube.

• 품질경영학회지
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• 제45권4호
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• pp.889-902
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• 2017

Purpose: The orthogonality and trace optimal properties are desirable for constructing designs of experiments. This article focuses on the determination of the sizes of experiments for the balanced trace optimal resolution-V fractional factorial designs for 2-level factorial designs, which have near-orthogonal properties. Methods: In this paper, first we introduce the trace optimal $2^t$ fractional factorial designs for $4{\leq}t{\leq}7$, by exploiting the partially balanced array for various cases of experimental sizes. Moreover some orthogonality criteria are also suggested with which the degree of the orthogonality of the designs can be evaluated. And we appraise the orthogonal properties of the introduced designs from various aspects. Results: We evaluate the orthogonal properties for the various experimental sizes of the balanced trace optimal resolution-V fractional factorial designs of the 2-level factorials in which each factor has two levels. And the near-orthogonal 2-level balanced trace optimal resolution-V fractional factorial designs are suggested, which have adequate sizes of experiments. Conclusion: We can construct the trace optimal $2^t$ fractional factorial designs for $4{\leq}t{\leq}7$ by exploiting the results suggested in this paper, which have near-orthogonal property and appropriate experimental sizes. The suggested designs can be employed usefully especially when we intend to analyze both the main effects and two factor interactions of the 2-level factorial experiments.

• Communications for Statistical Applications and Methods
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• 제16권1호
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• pp.195-208
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• 2009

A conventional single design optimality criterion has been used to select an efficient experimental design. But, since an experimental design is constructed with respect to an optimality criterion pre specified by investigators, an experimental design obtained from one optimality criterion which is superior to other designs may perform poorly when the design is evaluated by another optimality criterion. In other words, none of these is entirely satisfactory and even there is no guarantee that a design which is constructed from using a certain design optimality criterion is also optimal to the other design optimality criteria. Thus, it is necessary to develop certain special types of experimental designs that satisfy multiple design optimality criteria simultaneously because these multi-optimal designs (MODs) reflect the needs of the experimenters more adequately. In this article, we present a heuristic approach to construct second-order response surface designs which are more flexible and potentially very useful than the designs generated from a single design optimality criterion in many real experimental situations when several competing design optimality criteria are of interest. In this paper, over cuboidal design region for $3\;{\leq}\;k\;{\leq}\;5$ variables, we construct multi-optimal designs (MODs) that might moderately satisfy two famous alphabetic design optimality criteria, G- and IV-optimality criteria using a GA which considers a certain amount of randomness. The minimum, average and maximum scaled prediction variances for the generated response surface designs are provided. Based on the average and maximum scaled prediction variances for k = 3, 4 and 5 design variables, the MODs from a genetic algorithm (GA) have better statistical property than does the theoretically optimal designs and the MODs are more flexible and useful than single-criterion optimal designs.

• 대한안전경영과학회지
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• 제7권5호
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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.

• 한국가구학회지
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• 제23권1호
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• pp.1-9
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• 2012

Sustainable furniture designs are expressed through reutilization, reuse or redesign of the whole of part of natural materials and existing products. These designs contain natural emotions and show those propensities such as uncertainty, integrity, essentiality and experimental natures. Designs that use natural materials such as wood, bamboo, cork, plants, stones and water have sufficient beauty in themselves and thus these materials are not specially processed but their essence is pursued in those designs. Of those materials, the natural material water is used to pursue the essence of aqua while presenting a new furniture design through an experimental method. The circularity of aqua shares its meaning with the circularity of sustainable designs. In addition, the liquidity of aqua will be grafted onto IT technology to express variable shapes in order to present a new direction of furniture designs.

• 응용통계연구
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• 제10권1호
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• pp.163-175
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• 1997

많은 산업체나 농업 현장에서 실험이 행해질 때 블록내 실험단위에서의 처리가 시간적 또는 공간적으로 제약을 받는 경우가 빈번히 발생하게 되는데 이러한 경우 처리는 확률화에 따르기보다는 조직적인 순서에 따라 행해지게 된다. 이때 처리 효과가 블록내에서 나타날 수 있는 시간적 또는 공간적 추세에 독립적으로 추정되도록 순서가 설계된 실험계획을 추세무관 블록계획이라 부른다. 본 논문에서는 먼저 추세무관 블록계획의 성질을 살펴 그 필요성에 관해 약술하고 다음으로 선형추세무관 블록계획의 생성을 위한 두 알고리즘을 소개한다. 하나는 Bradley와 Odeh(1988)에 의해 고안된 알고리즘을 보완하였고, 다음은 존재하는 모든 가능한 계획을 발생시키는 알고리즘을 제시하였다.

• 생물정신의학
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• 제19권4호
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• pp.159-163
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• 2012

An appropriate research design for hypotheses and purposes leads to a good quality of research results. In this review article, we summarized the types of research methods and described the characteristics of clinical trials. Research designs are categorized into observational studies and experimental ones, depending on data collecting methods. In an observational study, there are cross-sectional, cohort and case-control studies. Parallel groups design and crossover trial studies are representative designs in a randomized controlled trial study, a kind of experimental study. Clinical researchers should understand the characteristics of clinical research designs including advantages and disadvantages and choose the suitable design according to their study purposes and the nature of collected data or subjects.

• 응용통계연구
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• 제13권2호
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• pp.477-488
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• 2000

전산실험계획으로 유용하게 쓰이는 라틴-하이퍼큐브 계획간의 거리를 정의하고 그 기대값을 계산하였다. 이 계산을 위해서 차원이 증가함에 따라 수리 통계학적 방법, 수치 해석적 방법(다차원 수치 적분법), 몬테카를로 적분 방법, 극한 정규분포이론을 이용하여 거리의 기대값을 구했다. 또한 같은 구조를 가지면서 랜덤성에 차이가 있는 두 라틴-하이퍼큐브 계획 간에 반응함수의 평균에서의 차이 및 정보량의 차이를 다루었다. 본 논문에서 제시한 두 Lhd들간의 비교 기법은 두 개의 일반 실험계획의 비교에도 유용하리라 여겨진다.