• Journal of Korean Society for Quality Management
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• v.38 no.1
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• pp.42-51
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• 2010

For the fractional factorial designs, the resolution-IV designs can be used when we want to estimate the main effects and to investigate the structure of the non-negligible two-factor interaction effects, when the three-factor and higher order interaction effects are all negligible. However we need to add the additional treatment combinations in order to identify the influential interactions for the resolution-IV fractional factorial designs. In this paper we investigate the statistical structure for 3-level resolution-IV designs constructed by fold-over scheme and introduce a method for analyzing the influential two-factor interactions.

• Journal of the Korean Statistical Society
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• v.35 no.2
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• pp.201-212
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• 2006

The technique of foldover is usually used by experimenters to de-alias the effects that are interesting in follow-up experiment. Employing a $2^{k-p}$ design with resolution III or higher, Li and Lin (2003) developed an algorithm and used computer programs to search its corresponding optimal foldover design for selected 16-run and 32-run experiments. Based on the minimum aberration criterion, the strong combined-optimal design, defined by Li and Lin, is the better choice of the initial design. In this article, we apply the technique of blocking to find the strong combined-optimal designs. Furthermore, we will tabulate all 16-run and 32-run strong combined-optimal designs and their corresponding core foldover plans for practical use. Some new designs that have not appeared in the other literature but constructed by the technique of blocking are also proposed in this article.

• 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 Korean Society for Quality Management Conference
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• 2010.04a
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• pp.129-138
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• 2010

For the fractional factorial designs, the resolution-IV designs can be used when we want to estimate the main effects and to investigate the structure of the non-negligible two-factor interaction effects, when the three-factor and higher order interaction effects are all negligible. However we need to add the additional treatment combination in order to identify the influential interactions for the resolution-IV fracrtional factorial designs. In this paper we investigate the statistical structure for 3-level resolution-IV designs constructed by fold-over scheme and introduce a method for analyzing the influential two-factor interactions.