Hybrid Model Driven Optimal DoE

Experimental design is a key activity for planning and conducting experiments to deliver the essential process data to understand and optimize a process. DoE and factorial designs are considered “state of the art” and the industry standard – but is that still true?

Join Dr. Alessandro Butté, CEO of DataHow, as he explains how today’s “state-of-the-art” approaches using factorial designs are no longer optimal when used alongside emerging technologies such as AI and hybrid modelling.

Key topics will include:

• What are the limitations of factorial designs and what is “optimal”;
• How a different approach is required when using hybrid models;
• How to re-define optimality in the view of utility to the user;
• What is the role of Bayesian optimizations and how to adapt them to hybrid models;
• How we can support users to chose an optimal strategy to achieve their goals.