Mixture Design for Optimal Formulations

Mixture Design for Optimal Formulations – Stat-Ease course
Mixture Design for
Optimal Formulations
WHY MIXTURE DESIGN FOR OPTIMAL FORMULATIONS?
The Recipe for Success.
If you do product formulation, then standard factorial designs just don't work. You need the mixture
designs taught in Mixture Design for Optimal Formulations to experiment most effectively.
COURSE SET-UP
During this 2-day course theory will alternate with exercises on PC. Design-Expert software helps
you practice designing and analyzing mixture experiments throughout the course. The software
provides the power for generation of optimal designs, as well as sophisticated graphical outputs such
as trace plots. You will learn how these methods work and what to look for.
PRIOR KNOWLEDGE
Prior knowledge of DOE, basic statistics and Analysis of Variance (ANOVA) is recommended.
GUEST LECTURER
Trainer of this course is Pat Whitcomb, the founding principal and president of Stat-Ease, Inc..
Pat Whitcomb co-authored Design-Ease® and Design-Expert® software. In addition, Pat is coauthor of the books, "DOE Simplified: Practical Tools for Effective Experimentation" and "RSM
Simplified: Optimizing Processes Using Response Surface Methods for Design of Experiments," and
has published many articles on design of experiments (DOE).
ORGANISATION
This course is co-organised by Stat-Ease, CQ Consultancy and StatSquare.
PRACTICAL
This course will be held on September 13 and 14, 2011, in the Convent of Chièvres, located in the
"Groot Begijnhof" (Grand Beguinage), Leuven's magnificent Unesco Heritage. The fee for attending
this 2-day course amounts to 1.000 Euro (excl. VAT), including handouts and lunches. Each course
day will be held from 9 am to about 5 pm.
To apply, please register on-line, latest 20 days before the start of the course.
CQ Consultancy, C. Meunierstraat 105, B-3000 Leuven, T: +32-16-441480, F: +32-16-441488, [email protected], www.cq.be
Mixture Design for Optimal Formulations – Stat-Ease course
COURSE CONTENTS
•
Introduction to Mixtures
o What makes a mixture ?
o Mixture (Scheffé) polynomials
o Gold jewelry
•
Unconstrained Mixtures
o Simplex-Lattice designs
ƒ Simplex without augmentation
ƒ Augmenting simplex designs
ƒ Augmented simplex lattice: yarn
•
Constrained Mixtures, Simplex
o Detergent formulation
ƒ Coding: Actual - Real - L_Pseudo
o Optimization of multiple responses
ƒ Numeric (desirability function)
ƒ Graphical (overlay plot)
o ABS pipe
ƒ Model reduction
ƒ Optimization
ƒ Piepel's versus Cox's direction
•
Constrained Mixtures, Non-Simplex
o Sizing for precision
o Constrained mixtures, extreme vertices: Shampoo
ƒ Optimal point selection: Flare
o Transformations: Antiseptic
•
Multicomponent Constraints
o Group constraints: Fruit punch
o Ratio constraints: Stability
o An additional equality constraint: Ice cream
•
Screening component
o Simplex: Additive package
o Non-simplex screening designs
ƒ Non-simplex screening exercise
o Review exercise: Blue haze
•
Special Mixture and Process problems
o Blocking a simplex design: olive oil
o Mixture amount experiments: Ibuprofen
o Mixtures with categorical factors: Auto coating
•
Summary
o Optional material (as time allows)
o Augmenting a mixture design: Sparklers
o Appendix
ƒ Sizing to detect a difference (details)
ƒ Piepel's versus Cox's direction (details)