P-value and interpretation of ANOVA Gage R & R

R

rdanis

#1
Hello,
I have downloaded a good Anova Gage R n R to conduct MSA.
I have collected the data with formula 10x3x3. But I don't
excatly how to interprete the result.
And also I don't understand about "p-value".

Please somebody help me to validate and interprete
the attached result.

I am also open for suggestion(s) and recomendation(s) for the next
action(s) to tackle the issue.:D.

Thankyou.
 

Attachments

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Miner

Forum Moderator
Staff member
Admin
#2
Read my blog on MSA, particularly parts 5a and 5b on R&R studies. There is a section on interpreting the results and graphs.

Regarding p-values, they indicate the probability that you would obtain these results purely by chance IF the null hypothesis were true. So exactly what does this mean and what are the implications?
  1. For the Parts, the null hypothesis is that there is no difference between parts. The p-value was 0.026. This is less than the TYPICAL cutoff value of 0.05, so we would reject the null hypothesis and say that there IS a difference between parts. This is a good thing. Our gauge should be able to distinguish between parts.
  2. For the Appraiser, the null hypothesis is that there is no difference between appraisers. The p-value was 0.000. This is less than the TYPICAL cutoff value of 0.05, so we would reject the null hypothesis and say that there IS a statistical difference between appraisers. This is usually a bad thing, especially if we have bad R&R results. This means that we need to work on improving appraiser to appraiser reproducibility.
  3. For the Appraiser part interaction, the null hypothesis is that there is no interaction between appraisers and parts. The p-value was 0.311, so we fail to reject the null hypothesis. This is a good thing because appraisers are measuring all parts the same way.
Your priority in making improvements should be the following:
  1. Focus on training Appraiser A to measure the same as Appraisers B & C. This will improve your Reproducibility which is the largest source of variation.
  2. Appraiser B has the least repeatability variation. Study their method, standardize that method and train the other two appraiser to use it.
 
R

rdanis

#3
Miner,
Thank you for reply. At first I want to ensure my management
that the current measurement system is not sufficient.
We are measuring PVC sheath (like rubber) with a digital caliper.
I believe the system will produce measurement error
but need to prove it factually.

Thank you for the link, I will read it on and continue
to study and may be will come back to this forum with
lot of questions.
 
R

rdanis

#5
It’s something I should give a try. Thanks again.
The blog entries are great but as english is not my mother tounge, I’m scare that I mis-interprete some entities of the posts. I’m also in doubt whether the previous GRR is valid or not as there is a chance the operators pull back the previous measurement data and align the new data to make them match.
So I reperform GRR as below.
It’s an extrusion process of cable sheath. I took a sample of processed sheath as usually and cut it into ten pieces. The spec is one side spec. I determine the measurement area so that all operators will measure the same place to minimize operator by part interaction. The measurement is done by the actual operators who perform the measurement process using the actual digi caliper. The caliper is calibrated.
At first I want to know about the measurement variation, if the result is fine, I will keep the measurement data daily for SPC X bar and R Chart. So, Do I select the sample in the correct way or not?
I am still getting a great total variation and both RR give almost the same contribution. Can I conclude the current measurement system is not qualified and could suggest to change the type of caliper? Do I perform the GRR the correctly?
Hope somebody would like to advice.
 

Miner

Forum Moderator
Staff member
Admin
#6
The only thing that I would do differently is the selection of the pieces. Extrusion processes are autocorrelated, which means that the measured value of one piece is dependent on the measured value of the piece prior to it. This means that you must allow time between samples to see true process variation.

I have prior experience with rubber extrusion, and found that I needed to allow 20 minutes between samples to obtain independent samples that exhibited true process variation.
 
R

rdanis

#7
Miner,
It's too costly to take sample every 20 minutes. It's not possible to cut the cable as it has standard length.
 
R

rdanis

#9
Well, it's not constant. It's depending on how long the customer ordering the cable. We process it drum by drum. I can say it takes hourly to switch to the next drums.
 
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