cancel
Showing results for 
Show  only  | Search instead for 
Did you mean: 
Choose Language Hide Translation Bar
elitesky
Level II

Which is the better custom DOE design?

I am designing a custom DOE with 8 factors (5 are continuous, 3 are categorical - 2 level). I would like to include all 2nd order interactions along with 4 center points. I am trying to decide between two options for DOE design:

 

1.) Including the 2nd order interactions in the model (48 runs total)

Using this method, JMP suggests a default of 48 runs. The color map on correlations looks great, with my 1st and 2nd order terms at 1 and everything else close to 0. However, the efficiencies are low (D = 82.5, G =  44.1, and A = 72.5). Also, average variance of prediction is 0.41. The prediction variance profiles give me a maximum variance of 1.85, and my fraction of design space plot ranges from 0.3 to 1.75.

 

2.) Including the 2nd order interactions as alias terms (48 runs total)

Using this method, JMP suggests a default of 20 runs, but I manually increase the number to 48 for direct comparison against option 1. The color map on correlations looks notably worse, with a significant number of terms close to 0.5. Everything else about the design looks better, though. Efficiencies are much higher (D = 95.3, G = 95.2, and A = 95.2). The average variance of prediction is 0.12. The prediction variance profiles give me a maximum variance of 0.20, and my fraction of design space plot ranges from 0.08 to 0.20.

 

Please help me to pick between the two options and let me know which of these design evaluation metrics are most important. Thanks!

10 REPLIES 10
elitesky
Level II

Re: Which is the better custom DOE design?

Thank you @statman@Mark_Bailey@P_Bartell, and @cwillden. Your comments have all been extremely helpful, and I feel I have a much better understanding of this custom design tool as well as how to proceed with the design. I would say we have a very good understanding of what we expect to happen based on years of experience in the field, so while we are screening for some effects, we have a good idea of how the others will impact the results. 

 

In reply to @cwillden, the efficiencies for Option 1 increase significantly if only taking into account the main effects (D = 93.8, G = 77.8, and A = 92.3). Also, as stated in my reply to @statman, when comparing Options 1 and 2 using all 1st and 2nd order effects, Option 1 is far superior.