Analyzing Data from Mixture Experiments Containing Process Variables: A Split-Plot Approach


Cornell, John A.   (1988, ASQC)   University of Florida

Journal of Quality Technology    Vol. 20    No. 1
QICID: 5600    January 1988    pp. 2-23
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Article Abstract

(This paper was presented at the Journal of Quality Technology Session at the 31st Annual Fall Technical Conference of the of the chemical and Process Industries Division of the American Society for Quality Control and the Section on Physical and Engineering Sciences of the American Statistical Association in Atlantic City, New Jersey, October 22-23, 1987.)

Many industrial experiments involve the blending of ingredients and the changing of process conditions to produce end products of highest quality. Such experiments are known as mixture experiments with process variables.This paper discusses the analysis of data generated from mixture experiments with process variables where the design is of the split-plot type. Two examples are given of experiments consisting of three mixture components and two process variables to illustrate the testing of hypotheses concerning the coefficients in the combined mixture components-process variables model.


Graphical methods,Design of experiments (DOE),Mixture experiments,Least squares,Interactions,Hypothesis testing

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