The application of RSM to design optimization is aimed at reducing the cost of
expensive analysis methods (e.g. finite element method or CFD analysis) and their
associated numerical noise. The problem can be approximated as described in
Chapter 2 with smooth functions that improve the convergence of the optimization
process because they reduce the effects of noise and they allow for the use of
derivative-based algorithms. Venter et al. (1996) have discussed the advantages of
using RSM for design optimization applications.
For example, in the case of the optimization of the calcination of Roman
cement described in Section 6.3, the engineer wants to find the levels of temperature
(x1) and time (x2) that maximize the early age strength (y) of the cement. The early
age strength is a function of the levels of temperature and time, as follows: