Modeling and Multivariate Methods - SAS

570 Visualizing, Optimizing, and Simulating Response Surfaces Chapter 24
The Profiler
Desirability Profiling for Multiple Responses
A desirability index becomes especially useful when there are multiple responses. The idea was pioneered by
Derringer and Suich (1980), who give the following example. Suppose there are four responses, ABRASION,
MODULUS, ELONG, and HARDNESS. Three factors, SILICA, SILANE, and SULFUR, were used in a
central composite design.
The data are in the Tiretread.jmp table in the Sample Data folder. Use the RSM For 4 responses script in
the data table, which defines a model for the four responses with a full quadratic response surface. The
summary tables and effect information appear for all the responses, followed by the prediction profiler
shown in Figure 24.17. The desirability functions are as follows:
1. Maximum ABRASION and maximum MODULUS are most desirable.
2. ELONG target of 500 is most desirable.
3. HARDNESS target of 67.5 is most desirable.
Figure 24.17 Profiler for Multiple Responses Before Optimization
Select Maximize Desirability from the Prediction Profiler pop-up menu to maximize desirability. The
results are shown in Figure 24.18. The desirability traces at the bottom decrease everywhere except the
current values of the effects, which indicates that any further adjustment could decrease the overall
desirability.