A response modeling approach to experimental design for optimal product design

The general problem considered is an optimization problem involving product design where some initial data are available and computer simulation is to be used to obtain more information. Resources and system complexity together restrict the number of simulations that can be performed in search of optimal settings for the product parameters. Consequently levels of these parameters, used in the simulations, (the experimental design) must be selected in an efficient way. We describe an algorithmic 'response-modeling' approach for performing this selection. The algorithm is illustrated using a rolamite design application. We provide (as examples) optimal one, two and three-point experimental designs for the rolamite computational analyses.