Use of Desirability Function Approach
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- This topic has 1 reply, 2 voices, and was last updated 9 months ago by
Robert Butler.
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- June 6, 2020 at 1:26 pm #248273
ce_seekParticipant@ce_seekInclude @ce_seek in your post and this person will
be notified via email.My study has multiple responses and for me to get the best result, I considered using a desirability function as an objective of the experiment. My question is, how will I know that there is no premature convergence happening? Thank you in advance for the help!
0June 6, 2020 at 2:12 pm #248274
Robert ButlerParticipant@rbutlerInclude @rbutler in your post and this person will
be notified via email.If you have multiple responses then presumably you have a predictive equation for each of those responses. If that is the case then you should have a minimum and a maximum level of desirability for each response. If this is true then take your equations – put them in a program, assemble the matrix of X’s and run the equations against the matrix. Next, tell the machine to sort through the predictions with the restrictions on minimum and maximum acceptable criteria for all of the responses (this done simultaneously) and find those that fall within your specifications.
What you will have will be a matrix consisting of settings and the corresponding predicted responses. Since it is very unlikely you will find a combination of X’s that gives you the best of everything you will have to look over the predictions and decide for yourself which set of X’s results in a group of predicted responses that are the “best”.
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