Can You Do a Design of Experiments with Different Levels for Different Factors?
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 This topic has 13 replies, 8 voices, and was last updated 3 years, 8 months ago by Chris Seider.

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January 8, 2019 at 9:08 am #211373
Tino VolpeParticipant@[email protected] Include @[email protected] in your post and this person will
be notified via email.I am trying to create a DOE with 2 factors, one factor having 2 levels and one factor having 3 levels. Is this possible. I’m pretty sure it can be done but I can’t figure out how.
Thanks
0January 8, 2019 at 11:04 am #211375
Chris SeiderParticipant@cseider Include @cseider in your post and this person will
be notified via email.By definition it’s not a factorial design that you’ve described. IF the 2nd of 3 levels for the 2nd factor is the “middle” setting of a machine or something, AND YOU INSIST ON LOOKING AT ALL 3, consider using the centerpoint approach for both factors. Highly depends on difficulty and expense to get the experimental runs.
0January 8, 2019 at 11:48 am #211377
Robert ButlerParticipant@rbutler Include @rbutler in your post and this person will
be notified via email.Sure, it’s a 2 x 3 design
Experiment Factor A Factor B
1 1 1
2 1 1
3 1 0
4 1 0
5 1 1
6 1 1
1January 8, 2019 at 11:50 am #211378
Robert ButlerParticipant@rbutler Include @rbutler in your post and this person will
be notified via email.Well, that’s just peachy. What you type isn’t what gets posted. Copy the design with headings into a word document and reinsert the appropriate blanks – you should have 3 columns, experimental number, levels for factor A and levels for factor B.
0January 8, 2019 at 5:20 pm #211389
Robert ButlerParticipant@rbutler Include @rbutler in your post and this person will
be notified via email.Thanks Katie(?), for correcting the design display on my first post. You can remove the second one if you wish.
0January 8, 2019 at 5:33 pm #211390
Michael CygerParticipant@michaelcyger Include @michaelcyger in your post and this person will
be notified via email.@rbutler: I fixed the formatting in your previous post so columns are displayed. Sorry for the trouble.
When content is posted that relies on spaces to display columns, please do the following:
1. Click the “code” button
2. Paste the table that is formatted with spaces
3. Click the “code button againThis wraps the content in formatting that properly maintains the width of characters.
Sorry to get off topic. Back to the DOE discussions! :)
0January 8, 2019 at 5:39 pm #211391
Robert ButlerParticipant@rbutler Include @rbutler in your post and this person will
be notified via email.Thanks Mike
1January 8, 2019 at 6:00 pm #211392
Katie BarryParticipant@KatieBarry Include @KatieBarry in your post and this person will
be notified via email.@rbutler – This exceeded my technical smarts, so I brought in Mike. :) Glad we were able to help!
0January 8, 2019 at 9:48 pm #211408
Mike CarnellParticipant@MikeCarnell Include @MikeCarnell in your post and this person will
be notified via email.Katie I think it is great you bring Michael every now and then. It keeps him occupied.
0January 9, 2019 at 7:34 am #211414
Tino VolpeParticipant@[email protected] Include @[email protected] in your post and this person will
be notified via email.thanks Robert. Can this be setup in Minitab 18?
0January 9, 2019 at 12:45 pm #211432
Robert ButlerParticipant@rbutler Include @rbutler in your post and this person will
be notified via email.I don’t understand what you mean by “setup in Minitab 18.” The six point design is all there is and it would just be a matter of building the appropriate spreadsheet for the X’s and Y responses. If you go with just the six points you can build a model where Y is a function of A, B, AB, and B*B. If you toss in a single replicate of one of the design points you could also check A*B*B.
You would reduce the model to just the significant terms in the usual way – first plot the data and see what you see, run backward elimination and forward selection with replacement regression and check the final model using residual analysis. If all is well then you would confirm the validity of the final reduced model by using it to make predictions with certain combinations of A and B, run those combinations, and see if your final result was inside the prediction error limits associated with your prediction.
If you have more than one Y you would follow the above procedure for each of them and then you would use all of the equations together to predict a couple of optimum conditions (these will most likely be trade offs – most of the time you can’t get all of the Y responses simultaneously at their optimum level for a given level of A and B) and you would test the predictions in the same manner as above.
0January 10, 2019 at 2:18 pm #211450
Jennifer AtlasParticipant@jennatlas Include @jennatlas in your post and this person will
be notified via email.Hello Tino,
To answer your question, you can do this in Minitab Statistical Software. Go to StatDOEFactorialCreate Factorial Design. Choose General Full Factorial, then when you select Design you can specify the number of levels for the different factors.
Minitab Technical Support is available to answer questions like this https://www.minitab.com/enus/contactus/
0January 14, 2019 at 12:55 pm #235307
Chris ButterworthParticipant@belfieldlad Include @belfieldlad in your post and this person will
be notified via email.Hi Tino,
Get a copy of Design and Analysis of Experiments by Douglas Montgomery. Chapter 5 will introduce you to factorial designs with some very good examples. What you are asking about is rather straightforward and wellexplained in Montgomery’s book.
0January 15, 2019 at 12:25 am #235322
Chris SeiderParticipant@cseider Include @cseider in your post and this person will
be notified via email.Don’t interpret my comment that you have to do a factorial design but checking for linearity is powerful depending on the needs.
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