JMP^®: Design and Analysis of Mixture Experiments

Learn how to:

• Use factorial-type designs in mixture scenarios.
• Design mixture experiments using traditional and advanced design strategies.
• Properly analyze and interpret formulation experiments.
• Characterize response behavior over the formulation space with a model.
• Find optimal formulations.

Introduction to Mixture Designs

• Review of experimental design principles.
• Using factorial designs for mixture scenarios.

Mixture Scenarios without Constraints for Linear Responses

• Define the Scheffé model for the linear response.
• Use simplex-lattice designs and simplex-centroid designs for mixtures with linear response.
• Use custom designs for mixtures with linear response.
• Analyzing mixture experiments.

Mixture Scenarios with Constraints for Linear Responses

• Accommodate constraints within and among mixture components.
• Use pseudo-component coding to reduce imposed collinearity.
• Use custom design for mixtures with constraints.

Mixture Designs for Nonlinear Response

• Define the Scheffé model for the nonlinear response, including cubic models.
• Augment initial design for mixtures with nonlinear response.
• Use simplex-lattice design, simplex-centroid design, and ABCD design.
• Use custom design.

Advanced Mixture Scenarios

• Define and interpret the Cox model.
• Combine process factors with mixture components in the same design.
• Design experiments for "mixtures within mixtures."
• Use and interpret Snee screening simplex design.
• Study space-filling designs for mixture experiments.