Free ENBIS Webinar by Pietro Tarantino on "A Sequential and Pragmatic Approach to Components Design Optimization by Computer Experiments"

20 November 2015; 12:45 – 13:30; Webinar

Pietro Tarantino will talk about sequential optimization of components design. The webinar will be moderated by Shirley Coleman.

Experimentation is an integral part of any development process. Since the formal introduction of computer experiments by Sacks et al. (1989), substantial work has been done to make these experiments as efficient and effective as possible and, as a consequence, more and more industrial studies are performed by replacing physical experimentation with a “virtual” one in which a computer runs a program that simulates the behaviour of the system of reference. There is no unique approach to design and analysis of computer experiments. Traditionally, space filling or optimal designs have been used for exploring the design region while polynomial regressions and Kriging models have been extensively used to build the meta-model or emulator. Recently sequential strategies have been introduced with the aim of reducing the experimental effort while keeping the required accuracy from the experiment. They consist in building a fairly accurate meta-model based on a low number of experimental points, and then adding new points in an iterative way by updating each time the meta-model according to a selected strategy like improving the accuracy of meta-model itself or finding the optimal design point in the design space.

In this webinar, a hybrid approach to achieve both meta-model accuracy and optimum design solution while keeping low the experimental effort is presented. The proposed methodology is applied to a practical and complex industrial case study.  The pragmatism of such strategy, together with simplicity of implementation promotes the generalization of this approach to other industrial experiments.