Mixture Design of Experiments Using JMP
Duration: 1.0 day CEU: 0.6
This course discusses basic and advanced concepts related to the design and analysis of mixture experiments. It presents simplex lattice designs, simplex centroid designs, extreme vertices with linear constraints, and custom mixture designs with other independent factors.
Learn how to
- select factors and responses for a mixture design of experiments
- create and analyze simplex lattice designs and simplex centroid designs
- create and analyze extreme vertices designs with linear constraints
- create and analyze optimal and custom mixture designs.
Who should attend
Engineers and scientists who have completed design-of-experiments training and want to design and analyze mixture experiments available in JMP softwarePrerequisites
Before attending this course, you should have completed the JMP Software: Statistical Data Exploration course. Other suggested courses include the JMP Software: ANOVA and Regression course and the JMP Software: Design and Analysis of Experiments course. However, the additional courses are not required.Course Contents
Introduction- general use and definition of mixture designs
- selecting factors and responses for mixture designs
- simplex lattice design definition
- design demonstration, analysis, and exercises
- simplex centroid design definition
- ABCD design definition
- design demonstration, analysis, and exercises
- extreme vertices design definition
- design demonstration, analysis, and exercises
- optimal design definition
- custom mixture design definition
- integration of dependent and independent factors into one experiment
- design demonstration, analysis, and exercises