Dear @Victor_G
Thank you very much for your reply,
It is indeed true that the recommended design for 8 factors (5 hard-to-change, 3 easy-to-change, only ME for HTC and ME+2nd for ETC) gives 24 runs and 8 whole plots.
However, when I increased the number of runs to 32, so one additional easy-to-change factor combination per whole plot, I noticed an improvement in the prediction variance, a reduction in the average correlation and a better D-efficiency. Since doing an extra experiment per whole plot is feasible, and for most substrates there is more than enough material to execute all experiments, I opted to go for the design with 32 runs.
Unfortunately, for 1 substrate I lack sufficient material to do all 32 runs. So, the idea was to select for this 1 substrate only 24 runs out of the 32 in the design (remember, in this experiment every run corresponds to an adhesive formulation). Then the question still is, how to best select which runs to drop, and which to retain for that one substrate.
As an alternative I could go for the recommended design of 24 runs for all substrates, but it seems to be a pity that I lose the improvements associated with the 8 extra runs. Unless of course, and that is for me difficult to assess, that the benefits in terms of effect estimation and significance testing when going to 32 runs would only be marginally better than that of the 24-run design.
Custom design 2 = 32 runs
Custom design 3= 24 runs