• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.487-493
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• 2011

The paper reviews three Split Plot Designs (SPDs) of fixed factors, and those are SPD (RCBD, RCBD), SPD (CRD, RCBD) and SBD (Split Block Design). RCBD (Randomized Complete Block Design) and CRD (Completely Randomized Design) are used to deploy whole plot and sub plot. The models explained in this study are derived from random, crossed and nested models.

• Proceedings of the Safety Management and Science Conference
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• 2009.11a
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• pp.649-657
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• 2009

The paper presents the measurement split split-plot models for saving the time and cost. The split split-plot designs developed are efficiently used to estimating the gauge R&R(Reproducibility & Repeatability) when the completely randomized design of all factors(such as high pressure and temperature) is expensive and time consuming. The models studied include three split split-plots considering the type of experimental units.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.61-69
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• 2005

In conducting the analysis of variance for the split-plot design using the statistical package SPSS, users including statisticians are faced with difficulties because of no appropriate example in the SPSS applications guide book. In this paper, therefore, we present an analysis of variance procedure for the split-plot design using SPSS syntax window.

• Proceedings of the Safety Management and Science Conference
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• 2012.04a
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• pp.277-292
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• 2012

The research presents an application of Balanced ANOVA (BANOVA) by utilizing randomized orders for various Split-Plot Designs (SPDs) which include two cell designs, split-plot with one-way HTC (Hard to Control) factor, split-plot with two-way HTC factor, split-split-plot design and nested design. In addition, four MINITAB examples of 2-level split-plot designs based on the number of blocks and the type of whole-plots are presented for practitioners to obtain comprehensive understanding. Furthermore, the geometrical interrelated properties among three typical Designs of Experiments (DOE), such as Factorial Design (FD), Response Surface Design (RSD), and Mixture Design (MD) are discussed in this paper.

• Journal of Industrial Technology
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• v.31 no.A
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• pp.27-31
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• 2011

In many industrial experiments, some practical constraints often force factors in an experiment to be much harder to change than others. Such an experiment involves randomization restrictions and it can be thought of as split-plot experiment. This paper investigates the path of steepest ascent/descent within a split-plot structure. A method is proposed for calculating the coordinates along the path.

• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.481-486
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• 2011

The research reviews three experimental designs which include Split Plot Design (SPD), Crossover Design (CD) and Replicated Design (RD) by using Latin Square Design (LSD). SPD (CRD, LSD) and SPD (LSD, RCBD) that are derived from (S:A)${\times}B{\times}C{\times}D$ and $A{\times}B{\times}C{\times}D$. In addition, (S:A)${\times}B{\times}C$, (S:A)${\times}C{\times}D$ and (S:A)${\times}B{\times}C{\times}D$ can be used to generate various LSD and CD models. Finally, Replicated LSDs are considered to increase the power of detectability.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.143-152
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• 2017

Restriction of completely randomization within a block can be handled by a split plot factorial design splitted by several plots. $3{\times}3$ split plot factorial design with two fixed main factors and one fixed block shows that powers of the rank transformed statistic for testing whole plot factorial effect and split plot factorial effect are superior to those of the parametric statistic when existing effect size is small or the remaining effect size is relatively smaller than the testing factorial effect size. Powers of the rank transformed statistic show relatively high level for exponential and double exponential distributions, whereas powers of the parametric and rank transformed statistic maintain similar level for normal and uniform distributions. Powers of the parametric and rank transformed statistic with two fixed main factors and one random block are respectively lower than those with all fixed factors. Powers of the parametric andrank transformed statistic for testing split plot factorial effect with two fixed main factors and one random block are slightly lower than those for testing whole plot factorial effect, but powers of the rank transformed statistic show comparative advantage over those of the parametric statistic.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.4
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• pp.223-227
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• 2009

The study presents two measurement split-plot models with a restricted randomization to save cost and time. Split-plot models are used to handle HTCM (Hard To Control Measurement) factors such as high temperature and long-time catalyst control. The models developed are represented by the processes for estimating the measurement precisions, that is, gauge R&R. The study also introduces three-step procedures to indentify resolution, improve R&R reduction, and evaluate the precision effect.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.651-658
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• 2018

Purpose: The algorithm described in Lim(1998) is available to determine the sample size directly given specified significance level, power and signal-to-noise ratio. We research on the efficient determination of the sample size by visual methods. Methods: We propose three graphs for investigating the mutual relationship between the sample size r, power $1-{\beta}$ and the detectable signal-to-noise ratio ${\Delta}$. First graph shows the relationship between ${\Delta}$ and $1-{\beta}$ for the given r and it can be checked whether the power is sufficient enough. Second graph shows the relationship between r and ${\Delta}$ for the given power $1-{\beta}$. Third graph shows the relationship between r and $1-{\beta}$ for the given ${\Delta}$. It can be checked that which effects are sensitive to the efficient sample size by investigating those graphs. Results: In factorial design, randomized block design and the split plot design how to determine the sample size directly given specified significance level, power and signal-to-noise ratio is programmed by using R. A experiment to study the split plot design in Hicks(1982) is used as an example. We compare the sample sizes calculated by randomized block design with those by split plot design. By using graphs, we can check the possibility of reducing the sample size efficiently. Conclusion: The proposed visual methods can help an engineer to make a proper plan to reduce the sample size.

• Journal of the Korea Safety Management & Science
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• v.10 no.1
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• pp.191-195
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• 2008

The present study contributes reviewing and suggesting various models for measurement system analysis (MSA). Measurement errors consist of accuracy, linearity, stability, part precision, repeatability and reproducibility (R&R). First, the major content presents split-plot design, and the combination method of crossed and nested design for obtaining gage R&R. Second, we propose $\bar{x}-s$ variable control chart for calculating the gage R&R and number of distinct category. Lastly, investigating the determination of gage performance curve which establishes the control specification propagating calibration uncertainties and measurement errors is described.