What is importance in response optimization?

The importance determines the relative importance of multiple response variables.

Often, there is no factor setting that maximizes the desirability of the individual responses at the same time. That is why you maximize the composite desirability. The importance determines how much effect each response has on the composite desirability.

Should I modify the importance values of the responses?

You need to assess the importance of each response in order to assign appropriate values for importance. Values must be between 0.1 and 10. If all responses are equally important, use the default value of 1 for each response. The composite desirability is then the geometric mean of the individual desirabilities.

However, if some responses are more important than others, you can include this information into the optimal solution by setting unequal importance values. Larger values correspond to more important responses, smaller values to less important responses.

You can also change the importance values to determine how sensitive the solution is to the assigned values. For example, you may determine that the optimal solution when one response has a greater importance is very different from the optimal solution when the same response has a lesser importance.

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