fractional factorial experiment

fractional factorial experiment

[¦frak·shən·əl fak¦tȯr·ē·əl ik′sper·ə·mənt]
(statistics)
An experiment in which certain properly chosen levels of factors are left out. Also known as fractional replicate.
McGraw-Hill Dictionary of Scientific & Technical Terms, 6E, Copyright © 2003 by The McGraw-Hill Companies, Inc.
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According to Wen Li (2015), there are different statistical methods available for factor screening, such as one-factor-at-a-time method, Taguchi's method, application of full factorial experiment design, fractional factorial experiment design, as well as Plackett-Burman designs.
From ANOVA results for fractional factorial experiment, the first central rotational composed design was used to optimize or verify optimization tendency of protein extraction from flour.
Hahn, Morgan and Schmee[6] applied the iterative least squares approach to analyse the results of a fractional factorial experiment involving censoring to the left.
There are two types of screening experiments, a sensitivity analysis and a fractional factorial experiment. In a sensitivity analysis, all circuit parameters (factors) are held at their nominal values, except one, which is set to its high value for one simulation, and its low value for another.
All of these decisions were based on data generated by the fractional factorial experiment.
Fractional factorial experiments combined with insightful qualitative evaluations to explain success and shortcomings in care delivery innovations may offer the best chance of supporting evidence-based continuous improvements, not only for providers but for the Medicare program itself.
The paper demonstrates use of tools such as the IPO (Input-Process-Output) diagram, Cause and Effect Diagram, Fractional Factorial Experiments and Full Factorial Experiments.
The fractional factorial experiments plan is based on the idea that certain possible combinations of factors provide enough efficient information, so that the number of effective experiments may be considerably reduced.
Researchers typically use fractional factorial experiments to narrow a collection of many suspect variables down to a few significant variables and identify the variables that warrant further investigation while screening out variables that do not.
Day two dealt with review of factorial experiments, blocking experiments, fractional factorial experiments, half fractions, quarter fractions, saturated designs, and an introduction to response surface methodology.
Initial concentrations of Cd, Cu, Ni, and Zn, expressed as mM, in the fractional factorial experiments Run Cd Cr Cu Ni Zn Calcixerollic Xerochrept 1 4.95 6.62 0 0 0 2 0 6.62 14.5 8.11 0 3 0 6.62 14.5 0 7.34 4 4.95 0 14.5 8.11 0 5 0 0 0 8.11 7.34 6 4.95 6.62 0 8.11 7.34 7 4.95 0 14.5 0 7.34 8 0 0 0 0 0 Paralithic Xerorthent 1 6.23 3.62 13.2 0 0 2 0 3.62 13.2 2.32 14.2 3 6.23 0 13.2 2.32 0 4 0 0 13.2 0 14.2 5 6.23 3.62 00 14.2 6 0 3.62 0 2.32 0 7 6.23 0 0 2.32 14.2 8 0 0 0 0 0
Experimental Design - Initial runs were made on a [TABULAR DATA FOR TABLE 1 OMITTED] screening basis, followed by use of Taguchi-type fractional factorial experiments to evaluate the importance of the four variables, and their interactions.

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