Hi Victor!
Thank you for your detailed response and for the breakdown of variance sources, I found it incredibly helpful.
1- Model variance wasn't something I considered but is an excellent point! What's interesting when looking at this is that one of the recommended factors that the model suggested based on my desirability criteria falls into a range where the model variance is highest. I'm not sure if this should be a concern given that the ANOVA and lack of fit analyses of my model suggest that the model is well fitted and can use the input factors to predict the response.
2 and 3. This is exactly what I'm looking for - the only issue here is expense, ideally I'd like to repeat every experimental run but I simply will not have the resources to do so. Is there anyway to select certain points that I can model that will allow me to assess the response + input variance?
Thank you for your help and suggestions thus far!