Taguchi method using Minitab - DOE (Design of Experiments) Help

P

Prototype

#1
Hi

Please see the attachment foe the DOE problem. I've used Taguchi method using Minitab to analyze the matrix. Can someone tell me what the results mean? I've posted the question in the attachment.

Thanks a lot.
 

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Miner

Forum Moderator
Staff member
Admin
#2
No. You are analyzing count data that cannot be less than zero. Minitab does not know this. It assumes the data is continuous with no lower boundary.

If I were analyzing this data, I would use the Freeman-Tukey transform for count data then analyze using classical techniques. The S/N approach complicates and muddies the analysis.
 
P

Prototype

#3
No. You are analyzing count data that cannot be less than zero. Minitab does not know this. It assumes the data is continuous with no lower boundary.

If I were analyzing this data, I would use the Freeman-Tukey transform for count data then analyze using classical techniques. The S/N approach complicates and muddies the analysis.
I'm not aware of the Freeman-Tukey method. If I'm understanding you correctly, because counting the number of defects is an attribute and minitab doesn't know this you cannot predict the number of defectives at the optimum setting using Taguchi method. Am I right?

Thanks for the reply though
 
L

Lemor - 2011

#4
minitab interpreted optimim setting as higher is better. your condition is smaller is better
 
M

Mustafainisb

#5
Dear Moderator,
pl tell me how to raise my problem in this forum.
Dear listners,
I have four factors and three levels (L9) with three times repeat laser cutting process on the same input setting and measure kerf width(smaller the better) . One of the input data set produce unsuccessful cutting of sheet by laser. So if i take zero than signal to noise ratio is infinite. What is the practice of analyst to represent uncut value?

Best Regards

Mustafa Zaidi
 

Miner

Forum Moderator
Staff member
Admin
#6
I am not a proponent of S/N ratio. I prefer to analyze the mean and StDev separately using classical methods.

In your case, you have missing data, or what is sometimes called botched runs. Your best bet is to try to analyze the data that you do have using GLM or Regression analysis.

You could also try an RSM approach using a Face centered or Box-Benken design or even an Optimal design to avoid the setting that are not feasible.
 
M

Mustafainisb

#7
Dear ,
Thanks for reply, the problem is write know that i have full factorial design data so it is difficult to perform it again free from Malaysia. So what i can do if i want to do analysis. i am thinking that these values of uncut should be deleted but the observation table will be unbalanced. So how i can handle it. for calculating interactions.
 
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