Discover the secrets to customizing your experiments using optimal designs. When standard (canned) response surface designs are unsuitable due to operational or physical constraints, optimal (custom) designs may be the answer. During this webinar, gain a greater understanding of the statistical and practical differences between D and I-optimality. Learn the importance of considering multiple criteria when building an optimal design, such as adding lack of fit points and replicates. All these issues are considered at a practical level – keeping the actual experimenters in mind. This brings to the forefront such considerations as subject matter knowledge (first principles), factor choice, and the feasibility of the experiment design.
Pat Whitcomb details the cost-saving mixture-process models developed by Scott Kowalski, John Cornell and Geoff Vining (KCV). Design-Expert® software, version 12, drops this modeling tool right into the user's hands. See how it reduces the number of model terms and thereby reduces the number of runs required to estimate the complex relationship between mixture and process variables. Estimated length: 45 min.
Discover how to optimize your process while avoiding impossible factor combinations.
Discover how propagation of error and tolerance analysis can account for variation in your system.