Mixture and Mixture–Process Variable Experiments for Paint Preparation Applications

Jian Hu

doi:10.4028/www.scientific.net/AMR.457-458.1465

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 457-458Mixture and Mixture–Process Variable Experiments...

Mixture and Mixture–Process Variable Experiments for Paint Preparation Applications

Abstract:

Many experiments in research and development in the paint preparation involve mixture components. These are experiments with mixtures in which the experimental factors are the components of a mixture and the response variable depends on the relative proportion of each components, but not on the absolute amount of the mixture. Thus the mixture components cannot be varied independently. A common variation of the mixture experiment occurs when there are also one or more process factors that can be varied independently of each other and of the mixture ingredients, to bring about a mixture–process variable experiment. We discuss the design and analysis of these types of experiments, using flame-retardant coating formulation as an example. Goal of this paper is to encourage greater utilization of these techniques in paint preparation research and development.

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Periodical:

Advanced Materials Research (Volumes 457-458)

Pages:

1465-1469

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.457-458.1465

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Online since:

January 2012

Authors:

Jian Hu

Keywords:

Analysis of Variance (ANOVA), Design of Experiment (DOE), D-Optimal Design, Mixture Experiments, Paint Preparation, Response Surface Methodology (RSM)

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References

[1] William G. Cochran, Gertrude M. Cox: Experimental Designs, 2nd Edition (John Wiley & Sons, New York 2009).

Google Scholar

[2] J.A. Cornell: Experiments with Mixtures: Designs, Models, and the Analysis of Mixture Data (John Wiley & Sons, New York 2002).

Google Scholar

[3] R.H. Myers, D.C. Montgomery: Response Surface Methodology: Process and Product Optimization Using Designed Experiments (John Wiley & Sons, New York, 2009).

Google Scholar

[4] Henry Scheffé: J. Roy. Stat. Soc. B Vol. 20 (1958), p.344.

Google Scholar

[5] J. S. Murty and M. N. Das: The Annals of Mathematical Statistics Vol. 39(1968), p.1517.

Google Scholar

[6] J.W. Gorman and J.E. Hinman: Technometrics Vol. 4(1962), p.463.

Google Scholar

[7] C.M. Anderson-Cook, H.B. Goldfarb, C.M. Borror, D.C. Montgomery, K.G. Canter and J.N. Twist: Pharmaceut. Statist. Vol. 3(2004), p.247.

DOI: 10.1002/pst.138

Google Scholar

[8] H.B. Goldfarb, C.M. Borror, D.C. Montgomery and C.M. Anderson-Cook: Journal of Quality Technology Vol. 36( 2004), p.109.

Google Scholar

[9] H.B. Goldfarb, C.M. Anderson-Cook, C.M. Borror and D.C. Montgomery: Journal of Quality Technology Vol. 36(2004), p.169.

Google Scholar

[10] Design-Expert® 8. 0 (Stat-Ease, Inc. ) on http: /www. statease. com.

Google Scholar