2003
DOI: 10.1007/s00163-002-0026-9
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A role for "one-factor-at-a-time" experimentation in parameter design

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Cited by 124 publications
(57 citation statements)
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“…2. The equation was very reliable with R 2 value of 0.9365 and low p values (p \ 0.1) of the model fit, which indicate a strong correspondence between theoretical predictions and experimental results [11,12]. The low coefficient of variation (CV) value of 7.956054 also represented that the differences between the predicted and the observed values were little.…”
Section: Pbd and Analysismentioning
confidence: 70%
See 1 more Smart Citation
“…2. The equation was very reliable with R 2 value of 0.9365 and low p values (p \ 0.1) of the model fit, which indicate a strong correspondence between theoretical predictions and experimental results [11,12]. The low coefficient of variation (CV) value of 7.956054 also represented that the differences between the predicted and the observed values were little.…”
Section: Pbd and Analysismentioning
confidence: 70%
“…However, such traditional optimization strategies (one-factor-at-a-time) require considerable time and effort [12]. More statistical approach such as the Plackett-Burman (PBD) and the Box-Behnken design (BBD) efficiently select the most significant components of the medium and rapidly evaluates the interactions between multiple components [13].…”
Section: Introductionmentioning
confidence: 99%
“…However, this method is timeconsuming, and interaction among the medium component cannot be studied (Mu et al 2009). The limitation of such method can be avoided by using statistical experimental design, a powerful and useful tool, which can allow explaining interactions between the different variables and decreasing the process variability (Frey et al 2003). The most popular choices are the Plackett-Burman design (PBD) and the central composite design (CCD), along with the response surface analysis (Liu et al 2005;Xu et al 2008).…”
Section: Introductionmentioning
confidence: 99%
“…Although OFAT leads to clearly expressed conclusions, the chance of missing optimum conditions and not observing the covariance between parameters is high in this approach. 15,16 Thus, existing results should be interpreted with caution, and the widely accepted hypotheses for the effect of synthesis conditions require further revaluation to be extrapolated to novel practices. In the current work, we present a systematic study of the effect of simultaneous changes of synthesis conditions on surface morphology, and permeation properties of TFC membranes.…”
Section: Introductionmentioning
confidence: 99%