Designing Experiments to Optimize Manufacturing Materials Selection
Design of Experiments
See how to design experiments based on physical or chemical properties to significantly minimize the number of required experimental conditions and produce a model that can predict untested options. These efficient designs are based on QSAR (Quantitative Structure – Activity Relationship) and a 2017 JMP Discovery Summit presentation by Silvio Miccio, Procter and Gamble.
This webinar covers: Using Principal Components Analysis (PCA) to compress information describing properties of potential options; using covariate properties to select materials to use in the experimental design; and modeling and comparing results to choose the most extensible model.