我笑着哭DX8-04F-MultifactorRSM-IVopt.docx Rev. 5/17/10
Multifactor RSM Tutorial
(Optimal design)
This tutorial details how Design-Expert® software crafts a response surface method (RSM) experiment within an irregular process space.
A food scientist wants to optimize a wheat product cooked at varying times versus temperatures. After a series of screening and in-depth factorial designs, the search for a process optimum has been narrowed to two factors, ranging as follows:
A. Temperature, 110 to 180 degrees C.
B. Time, 17 to 23 minutes.
However, it’s been discovered that to initiate desirable starch
gelatinization, time must be at least 19 minutes when temperature is at 110 degrees C – the low end of its experimental range. On the other hand, when the temperature is increased to 180 degrees the starch will gel in only 17 minutes.
Constraint at lower levels of factors
To recap: At the lowest level of A, factor B must be at least 19, while at the lowest level of B, factor A must be at least 180. To complicate matters further, the experimenter suspects that the response surface may be wavy. That is, the
standard quadratic model used for response surface methods (RSM) may fall short for providing accurate predictions. Therefore, a cubic model is recommended for the design.
A problem like this can be handled by Design-Expert® software via its constraint tools and optimal design capability.
Design the Experiment
on the left of the toolbar, or select File, New Design, or simply click New Design on our opening page.
Design-Expert 8 User’s Guide D-Optimal RSM Tutorial
1
