Three-Dimensional Variance Dispersion Graphs for Mixture-Process Experiments

Abstract

In a mixture experiment, the design factors are the proportions of the components of a mixture, and the response variables depend only on these component proportions. In addition to the mixture components, the experimenter may be interested in other variables that can be varied independently of one another and of the mixture components. Such mixture-process experiments are common in industry. There are many strategies based on different design criteria that are used to create designs involving both types of variables. We develop variance dispersion graphs (VDGs) to evaluate mixture-process designs and illustrate how the graphs are used with two examples.

• Mixture Experiments
• Prediction Variance
• Variance Dispersion Graphs

Additional information

Notes on contributors

Heidi B. Goldfarb

Dr. Goldfarb is a Principal Statistician in the Research and Development Department. She is a Member of ASQ. Her e-mail address is [email protected].

Connie M. Borror

Dr. Borror is an Assistant Professor in the Department of Decision Sciences. She is a senior Member of ASQ. Her e-mail address is [email protected].

Douglas C. Montgomery

Dr. Montgomery is a Professor in the Department of Industrial Engineering. He is a Fellow of ASQ. His e-mail address is [email protected].

Christine M. Anderson-Cook

Dr. Anderson-Cook is an Associate Professor in the Department of Statistics. She is a member of ASQ. Her e-mail address is [email protected].