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Staff
Initiation of the DOE Feedback Loop!

What is the DOE Feedback Loop, you ask?

The DOE feedback loop is a new initiative by statslikejazz (also known as me) and is brought into the world to make scientists and engineers more open about getting started with DOE.

So, how will the DOE Feedback work in practice? Well… As with everything in my life, it is not thoroughly thought through yet, but here is the Pitch.

I will create a DOE, and you will let me know if it fits your needs.

1) If YES, I am done (Yay)

2) if NO, I will make a new one based on your feedback!

Ok, that sounds like a never-ending story, but it is not! What I wish to create from this initiative is a decision tree where one can get to the design you need by answering a series of yes/no questions!

In the first DOE, I will cover all designs with 6 – 12 continuous factors and a single Y with no additional weird requirements.

So, if someone asks about that scenario, I will refer them to the original DOE.

Are we done? Are you telling me you have more than just continuous factors?

Let me know in the comments and the DOE feedback takes another round!

Level III

Hi Christian,
New case:

3 variables (factors)

Factor 1 (Continuous) = 0 - 225

Factor 2 (Continuous) = 0 - 10

Factor 3 (Discrete - 2 level) = 60 and 90 (process step)

Factor 3 can be considered as a final processing step for the mixture of the first 2 factors. So as an example:

Factor 1 (225) combined with Factor 2 (10) - this batch would be treated both at 60 and 90 the same day.

The limiting/challenging part is the number of batches that can be done pr. day. There is only time to mix 2 batches per day with a 8 days of trial in total. Meaning up to 16 batches and "32 unique runs".

I have tried different solutions with blocking/hard to change factors. However the power analysis comes out quite poor if I set both continuous factors as hard to change.

I am interested in a model that can explain the following:

The 3 main factors

All interaction terms

Factor 1 X Factor 1

Community Manager

@ChristianBille  there is a  comment from @Bertelsen92  above.  @Bertelsen92 , if you @mention the authors, they will see them immediately!

Level I

Hi ! Christian,

I have a case for you and I would like choose best design for this.

Here is the case;

5 factors with two levels,

Purpose of experiment is to find out the factor which impact the process output most and I have only one trial to set a experiment with Max of 12 treatments

Plz help me out to choose the best screening design to fulfill my goal.