Use Minitab's Response Optimizer to help identify the variable settings that optimize a single response or a set of responses. For multiple responses, the requirements for all the responses in the set must be satisfied.

Response optimization is often useful in product development when you need to determine operating conditions that will result in a product with desirable properties. For example, you may need to determine settings that optimize several properties of a product, such as its elasticity and puncture resistance.

A building materials manufacturer is developing a new insulation product for construction. They would like to study four variables that are believed to impact three quality characteristics of interest: insulative value (Insulation), density (Density), and strength (Strength) of the insulation. The four variables are:

·    material type (Material)

·    injection temperature (InjTemp)

·    injection pressure (InjPress)

·    cooling temperature (CoolTemp)

They also recorded the temperature at the time of the density measurement (MeasTemp), which is included as a covariate in the models for insulation, density, and strength.

Data: Insulation2.MTW (available in the Sample Data folder).