JMP Software: Design and Analysis of Mixture Experiments

This course is for JMP users who deal with mixture or formulation experiments. The course demonstrates how to utilize various approaches to create an appropriate experimental design for commonly encountered mixture situations. The analysis of mixture experiments is also covered including finding the optimum formulation.

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.

Who should attend

Individuals who work with formulations and need to plan their experiments and analyze the results

Formats available	Duration
Classroom:	1.0 day

Before attending this course, you should complete either the JMP Software: Classic Design of Experiments course or the JMP Software: Custom Design of Experiments course.

This course addresses JMP software.

Introduction to Mixture Designs

• review of experimental design principles
• using factorial-type designs for mixture scenarios

Basic Mixture Designs

• simplex-lattice design
• simplex-centroid design
• ABCD design

Analysis of Mixture Designs

• linear Scheffe model
• quadratic Scheffe model
• cubic Scheffe model
• Cox model

Advanced Mixture Designs

• constrained mixture designs
• analysis of constrained mixture designs
• combined mixture-process designs