A Case Study Involving Mixture-Process Variable Experiments within a Split-Plot Structure

Quality Engineering vol. 24 issue 1 - January 2012

Abstract: When an experiment involves both mixture and process variables, it can be necessary to restrict the randomization of experimental runs to reduce the size of the experiment. This results in a split-plot structure. If some process variables are noise variables, it is important to find a parameter setting that is robust to the variability of those factors. A real example of a mixture-process experiment within a split-plot structure is presented. The example is used to show that a dual optimization using both a mean model and a variance model can find the settings that are robust to the noise variables.

Keywords: Design of experiments (DOE); Mixture design; Noise; Optimal design; Robust design; Split-plot design

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