DOE – Advanced Designs and Topics
This course takes you to an advanced level with DOE. The topics cover Response Surface Design, used to model curvature and Screening Designs, used to screen variables when the process has too many dimensions. Also, the course explains how to manage particular advanced situations, such as hard to change factors, covariates and missing or strange values. Multi optimisation and cost optimisation complete the arguments of this advanced course.
Topics include
DAY 1:
- Introduction to Response Surface Design
- A deeper understanding of the concept of optimisation
- Guidelines and best practices for process optimisation
- Central composite design
- How to analyse data collected with Response Surface Design
- Augmenting a Factorial Design to a Central Composite Design
- Box-Behnken designs
- Sequential experimentation in practice
- Multiple response optimisation
DAY 2:
- Concept of repetitions and replicates
- Variance analysis with DOE
- Minimise variability and optimise response
- DOE with covariate variables
- Split-Plot designs for hard to change factors
- How to manage missing points in DOE
- Definitive Screening designs
What you will be able to do
- Design and run a Response Surface experiment
- Use DOE to find relevant variables in complex processes
- Optimise many responses at the same time
- Work with hard to change factors
- Design and run sequential experiments
Duration
1 or 2 days, depending on topics selected for training.
Pre requisites
- Basic Statistics
- DOE – Factorial Design
Available based on
- Minitab
- TIBCO Statistica
- R
Audience
This course is designed for those who have gained experience with factorial designs and wants go further in order to be able to use all the amazing approaches offered by DOE and get a full, professional view of design of experiment.
