When defining an engineering problem and choosing the variables, the region of interest called Design Space is framed. DOE techniques allow for the exploration of the design space by considering all variables simultaneously and predicting the system's response over a wide range of values.
The choice of the most suitable DOE depends largely on:
- the problem at hand
- the purpose of the exploration (e.g. optimization, RSM training, etc.)
- the available computational resources.
modeFRONTIER® offers a number of sophisticated and efficient DOE methods, which permit the efficient measurement of the design space dimensionality, and develop scientifically a series of simulation experiments.
Among those methods, Space Filler DOEs serve as the starting point for a subsequent optimization process or a database for response surface training. Statistical DOEs are useful to create samplings for the sensitivity analysis thus allowing in-depth understanding of the problem by identifying the sources of variation. Robustness and reliability DOEs help create a set of stochastic points for robustness evaluation. Optimal Designs DOEs are special purpose techniques used for reducing the dataset in a suitable way.
NEW > COMBINING FILLING STRATEGIES & RSM