Advanced Design of Experiments (1.0) Days

JMP Advanced DOE (1.0 days): This course builds on the DOE Using JMP material by providing more insight into the metrics of good designs such as prediction variance, power analysis, design optimality, and correlation between factors. We build on custom designs with constrained design regions/disallowed combinations and augmenting existing designs with new runs. We introduce new classes of designs useful in many practical applications: split plot designs (hard-to-change factors), space filling designs, mixture designs, and supersaturated (more factors than runs) designs.

JMP Advanced DOE Objectives:

• Understand the impact of power, prediction variance, optimality criterion (A, D, or I) and correlation/alias structure in designs
• Create custom designs in the presence of a constrained factor space
• Augment designs with additional runs taking advantage of what you learned from those tests already conducted.
• Know when to use and be able to construct split-plot designs, supersaturated designs, space filling designs, and mixture designs

Outline:

1. DOE review
   • Classical designs
   • Metrics of a good design
   • Custom designs and optimality criterion
2. Designs Methods
   • Constrained designs and disallowed combinations
   • Augmenting designs
3. Advanced Designs
   • split-plot designs
   • supersaturated designs
   • space filling designs
   • mixture designs