# How to Estimate the Number of Replicates on a DOE (Design of Experiments)

J

#### Jparfer

Hi there!

How can I calculate the number of replic i need to do in order to arrive to good conclusions and to get all the variability of the process?

#### optomist1

##### A Sea of Statistics
Super Moderator
Are you using Minitab software??

#### Miner

##### Forum Moderator
The answer is yes, but you will probably need a good software package. You need an estimate of the process standard deviation, the effect size that you wish to detect, as well as the alpha risk and power. Minitab has an easy to use Power and sample size calculator.

If you do not have a software package try this online ANOVA sample size calculator. You will have to go at it in a trial an error approach and the answer will be approximate, but should be close enough.

J

#### Jparfer

Yes, I?m using Minitab software

I have this menu, but i have some doubts in how to fill some fields:

Number of corner points: I think that is the numer of corners in the cube. For example, in a complete 2^3 = 8, and in a complete 2^4=16

Effects: I have no idea of how to fill it.

Can someone help me in this and give me the formula to stimate it?

Thanks!

S

#### supreecha

Power and Sample Size

Plackett-Burman Design

Alpha = 0.05 Assumed standard deviation = 0.5

Factors: 4 Design: 12
Center pts (total): 3

Including a term for center points in model.

Center Total Target
Points Effect Reps Runs Power Actual Power
3 0.75 2 27 0.9 0.938420
3 0.75 2 27 0.8 0.938420
3 0.75 2 27 0.7 0.938420
3 0.75 1 15 0.6 0.639023
3 0.75 1 15 0.5 0.639023
3 0.75 1 15 0.3 0.639023
3 0.75 1 15 0.2 0.639023
3 0.75 1 15 0.1 0.639023

Power Curve for Plackett-Burman Design

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#### Miner

##### Forum Moderator
Number of corner points: You are correct. This is the number of experimental runs, excluding replicates and center points.

Effect: this is set by you. How large or small of a process shift do you want to detect? It should be large enough that your boss would get excited and be willing to fund more experiments. Also, if this number is set to 1 standard deviation or smaller, the sample size rapidly increases.

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