4 Factors 3 Level DOE to determine which factors are significant

R

runvar

#1
#1
I am carrying out a DOE of experimental parameters to carry out experiments and determine which factors are significant for my experimental output.

The factors i have are voltage, duty factor, speed and gap and right now i have 9 iterations of the design.
I am new to Minitab and DOE and was wondering if what i have is correct or if i need to tweak it.
I have attached the spreadsheet with the iterations.
I have 2 output factors which i will measure after the experiments are done.
These will then be used to see which parameters affect the output favorably and non favorably.
 

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Miner

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#2
#2
I recommend using a 2-level fractional factorial with center points. See attached.

This is a more efficient approach to screening. If you detect curvature, you can add axial points to convert this to a response surface design. A 3-level design cannot be converted to RSM in Minitab.
 

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R

runvar

#3
#3
Miner thanks for the amazingly quick reply. :)

I just wanted to clarify on my question since i feel i may not have worded it correctly.
I will carry out experiments with different iterations with the 4 input factors that i have mentioned (Voltage, duty factor, speed, gap).
The output i am considering is width and height of the deposition.
There is no optimal value that i am looking at since these experiments havent been carried out before. I assume that for width a certain value is good and any experimental values close to that i get will mean that i can use those experimental parameters as ideal for carrying out experiments in the future.
Similarly for height i will do the same. By the end of DOE my objective is to say these levels of input factors affect the output (width and height) to have a very high value or a low value or an optimum value.

Forgive me if i am restating the same thing but i wanted to be doubly sure before i go about doing the experiments.
 
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