|
|
Response Optimizer
|
The optimization procedure picks several starting points from which to begin searching for the optimal variable settings. There are two types of solutions for the search:
By default, Minitab only displays the global solution.
Minitab calculates the individual desirability for each predicted response. The individual desirability values are then combined into the composite desirability. These desirability values can help you understand how close the predicted responses are to your target requirements. Desirability is measured on a 0 to 1 scale.
Individual desirability: The closer the predicted responses are to your target requirements, the closer the desirability will be to 1. The individual desirability for each response is displayed on the Optimization Plot.
Composite desirability: The composite desirability combines the individual desirabilities into an overall value, and reflects the relative importance of the responses. The higher the desirability the closer it will be to 1.
By default, Minitab places equal importance on the responses and assigns each an importance value of one. You can change the importance to allow some responses to have more influence on the composite desirability than other responses.
Example Output |
|
Solution
Hours Clump Discoloration Since Size of defects defects Composite Solution Cleanse Temperature Screw Fit Fit Desirability 1 0 80 small 5.66667 54.2279 0.429698 |
Interpretation |
For the resin defect data, the highest desirability occurs when the variables are as follows:
The minimum prediction for discoloration defects is not at these settings, but these settings provide the best achievable values for both responses simultaneously. The composite desirability places equal importance on both responses.
Free online chart generators for statistical analysis:
Useful tools: