• Journal of the Korean Statistical Society
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• 제31권3호
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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.

• 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.

• 공업화학
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• 제31권2호
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• pp.138-146
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• 2020

통계학적 실험계획법(DOE)은 수십 년 동안 산업계에서 품질을 개선하기 위해 사용되어온 방법이다. 본 연구에서는 화학공학 분야에서 통계적 실험계획법이 적용된 사례 115건을 검토해 보았다. 모든 사례는 지난 10년간 주요 과학저널에 발표된 내용이다. 적용되는 설계 유형, 실험 규모, 반응 변수에 영향을 미치는 요인 및 수준의 수 및 적용 분야가 분석되었다. 무엇보다 통계학적 실험계획법에 관련된 연구논문이 점차 증가하는 것을 알 수 있었다.

• 응용통계연구
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• 제33권1호
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• pp.87-105
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• 2020

통계공학은 실험계획법, 품질관리/품질경영, 신뢰성공학으로 구성된다. R은 무료로 개방되어 있는 통계패키지로서 통계모형, 통계 계산 및 통계 그래픽 관련 패키지가 방대하다. 우리는 이러한 R 패키지를 통계공학을 위한 기본 통계패키지로 유용하게 사용할 수 있다. 본 논문에서는 통계공학을 위한 R 패키지 응용을 살펴보고 통계공학 관련 CRAN Task Views가 필요함을 제안하였다.

• 응용통계연구
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• 제10권1호
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• pp.15-27
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• 1997

Randomized block design (RBD) with three replication is very frequently adopted in agricultural experiments of the Rural Development Administration of Korea. Even though it works well in field trials of traditional crops, it may not accomodate trial site conditions and/or experimental environment. In this research report, we deal with two such cases. The first case is for a crop experiment in green houses. In house conditions, RBD may not be appropriate since it cannot reflect two directions of the yield gradient. So, a Latin square design is suggested as an alternative. The second case is for local field experiments of the newly-inbred rice. RBD with three replications is used without doubt for decades, even though the site layout is not appropriately shaped for the design. In this case, we suggest the RBD in two blocks with multiple replicates for control varieties as an alternative. To improve the quality of statistical experimental designs in over one-thousand agricultural trials performed annually in the Rural Development Administration, we need to re-train agricultural researchers on the design and analysis of experiments and call for concerns of Korean statisticians.

• 응용통계연구
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• 제34권4호
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• pp.633-658
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• 2021

통계공학은 실험계획법, 품질관리/품질경영, 신뢰성공학으로 구성된다. Python은 무료로 개방되어 있는 패키지로서 머신러닝, 데이터사이언스, 공학 및 그래픽 관련 패키지가 방대하다. 우리는 이러한 Python 패키지를 통계공학을 위한 기본 패키지로 유용하게 사용할 수 있다. 본 논문에서는 통계공학을 위한 Python 패키지 응용을 살펴보고 통계공학 관련 종합 Python projects가 필요함을 제안하였다.

• 한국정밀공학회지
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• 제15권9호
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• pp.15-24
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• 1998

In this research. we have proposed a new technique to determine .the combination of design parameters for the process design of a hot forged product using artificial neural network(ANN) and statistical design of experiments(DOE). The investigated problem involves the adequate selection of the aspect ratio of billet, the ram velocity and the friction factor as design parameters. An optimal billet satisfying the forming limitation, die filling, load and energy as well as more uniform distribution of effective strain, is determined by applying the ability of artificial neural network and considering the analysis of mean and variation on the functional requirement. This methodology will be helpful in designing and controlling parameters on the shop floor which would yield the best design solution.

• Journal of the Korean Statistical Society
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• 제14권1호
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• pp.48-55
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• 1985

In clinical trials subjects are avalible sequentially and must be assigned to treatments immediately. Completely randomized procedure for the allocation of treatments to each subject may result in severe imbalance among the number of subjects in treatment groups, especially for small experiments or interim analyses of large experiments. In this study, restricted randomization methods such as biased coin designs (Efron, 1971), permuted block design, and truncated binomial design are compared to teh completely randomized design in the presence of selection and/or accidential bias by Monte Carlo simulations.

• Transactions on Electrical and Electronic Materials
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• 제10권5호
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• pp.177-181
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• 2009

Employing statistical design of experiments, we have performed studies on the characterization of electrodes using $TiO_2$ and process variables in the fabrication process of nanocrystalline dye sensitized solar cell. Systematic experiment to identify the effects of process variables on cell's efficiency has based on broad-band absorption of light by tailor made organometallic dye molecules dispersed on a high surface of $TiO_2$. Employing statistical design of experiment on $TiO_2$ photoelectrode forming process, structural characterization of electrodes and process variable have been investigated. Through the statistical analysis we have found that the particle size of $TiO_2$ and the amount of PEG/PEO are significantly affecting on the cell efficiency. In addition, a significant amount of interaction exists between the particle size and the amount of PEG/PEO.

• Journal of the Korean Statistical Society
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• 제11권1호
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• pp.36-44
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• 1982

A new design concept, called axis-slope-rotatability, is presented for the design of experiments with mixtures. This is an analogue of the Box-Hunter (1957) rotatability for second order response surface designs. By choice of design, it is possible to make the variance of the estimated slopes along the component axes constant for all axial points equidistant from the center point of the factor space. This property is called axis-slope-rotatability for mixture experiments. When the Scheffe's second degree polynomial is used, it is shown that some symmetry conditions are sufficient for axis-slope-rotatability. Several designs having this property are illustrated.