SAS Users Far and Wide,

I am new to SAS which we purchased to use for designing and analyzing experiments. A short while ago I posted a more complicated request and was delighted in the quality of the responses. I have not posted a summary because (1) I am still digesting that response, and (2) I wish to pursue the designing step further.

My question for today may seem easy to some, but I wish to have some of my assumptions verified.

A coworker wants to propose a study to help another division with a formulation. The formulation has a specification range, but the group doesn't understand the properties they might get at different combinations. As far as I know, there is only one response. I can't recall specifically, but it is a burning-property response for which the lab reports an average of three or more tests per sample (the reliability is unknown).

It's a flare composition with a three polymeric component binder and one metal, e.g., B1, B2, B3, and M1. The constraints are quite tight. B1 0.14-0.16 B2 0.14-0.16 B3 0.15-0.17 M1 0.52-0.56

My questions and assumptions:

The costs to prepare a "mix" is VERY expensive, so it's best to get the most from the least. It is preferred to generate a model and show a countour of the response for the customer. I am considering two approaches.

Using SAS's XVERT algorithm (McLean-Anderson), there are 39 observations in the full set. Of course, this is too many. If I am on the right track, there are six vertices. Following the quidelines of the algorithm, the centroid should be included and a few check points inside the design space. (Total 10 mixes so far.) Should there be a replicated point or two? Twelve mixes total is about the reasonable limit from a proposal standpoint...

But can we do it with less...

The constraints are very close, so wouldn't a linear model be good assumption. Again if I on the right track with this software, a five run design is generated for the linear model. It has four vertices and one point with the metal at its low value. The D-efficiency is 86.6. This approach would start with 5 runs; however, does it build a foundation for well planned follow-on runs to verify and better define the model? And what about the two-way interactions?

Thanks for you your patience and consulation while I am cutting my teeth on formulation experiments.

Warmest regards,

Mitch Gallant Chemist Naval Surface Warfare Center Indian Head, MD USA 301/743-4272 e-mail: mgallant@pilot.ih.navy.mil