# How to do Destructive Test Gage R&R - Rupture Test

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#### canhchi

Don Winton said:
Yea, I guess I should expound upon my last post. Sorry about that.
Would you please to send the interpolation from process capability numbers into R&R numbers to me by email?

Thanks and best regards,
Chi

#### Miner

##### Forum Moderator
I do not have this information readily available on the weekend, but you can derive it fairly easily.

Capability indices are based on the StdDev of the observed process variation.

The observed process variation is composed of the actual process variation and the measurement variation. This means that you may determine the actual process variation by removing the effect of the measurement variation.

The equation is:
(StdDev Actual)^2 = (StdDev Observed)^2 - (StdDev Measurement System)^2

Note: (StdDev)^2 is the StdDev squared (or the Variance).

You may now use StDDev Actual to calculate Cp actual (or another index).

You may use these calculations to develop a series of graphs that plot capability index observed to capability index actual along a line of a given measurement error. You can add additional lines of different measurement errors on the same graph.

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#### Lil' Nicky

I have a question regarding destructive attribute agreement analysis. I tried using the search but maybe I missed it...regardless I could use some help.

How do you set up your sample selection for a destructive attribute Gage R&R? Minitab requires two trials per appraiser, so how do you set that up given the criteria?

Any pointers or direction would be much appreciated!

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#### anpelim

The MSA shows the steps required to calculate the destructive GR&R Studies.
I found a way to get 11-18% GRR using a good lot/bad lot approach. Our company is accepting GR&R with 20% or less. Let's say that I'm getting values ranging from 50-100 lbs for the pull test (spec is 30 lbs min.). This variation is too high and we will likely have GRR's ranging from 90-100%. If I combine bad lots in the study with values ranging from 8-15 lbs, the GRR will decrease up to 12% in some examples I have.
We are pull testing silicon tubes, PVC syringes and also performing seal strength for pouches and packaging trays. All of the GRR studies are acceptable since they are giving 11% thru 18%.
If I'm doing anything wrong by reducing the variation this way, please let me know.

Super Moderator

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#### anpelim

I'm attaching two files. Dataset1.pdf has the data info for the pull test. The measurement column shows the odd rows with readings within specs and the even rows with reading below specs. The GRR results shows 13.5% GRR. Column C6 shows all readings within specs and a 100% GRR. The file named as chart1.pdf shows the charts for both Measurement and C6 columns. We deleted the "even" row values from C6 and replaced with values coming from bad lots (i.e.: 138.8 is a good lot, 22.9 is a bad lot, since the spec is 80 lbs min. That means if we combine good and bad lots we will highly reduce the variation for a GRR study.

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#### Bev D

##### Heretical Statistician
Super Moderator
I am confused...what constitutes your matched pairs?
you should be doign repeat measurements on the same part (or for destruct, portions of a part or sequentially produced parts if they can't be 'cut up')

what exactly makes the first and second reading per operator?

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#### anpelim

We are using one lot per reading. Parts are similar to the other ones.
Readings 1, 11, 21, 31 are coming from a "good lot"- Odd lot
Readings 2, 12, 22, 32 are coming from a "bad lot" - Even lot
and so on.
As you can see on the attached data, the variation on the "odd lots" is significantly higher than the "even lots", so the total variation is reduced.
You can compare that variation within trials and appraisers.

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#### anpelim

I forgot to mention that the way you setup the "bad" parts will determine the total variation. Let's suppose that the pull test requirement is 30 lbs minimum. You can test about 60 samples (2 operators, 3 trials). Since each trial will be 10 sample parts, then you will need to have the same quantity of good and bad parts for every trial (5 each).
The bad parts preparation will simulate an incorrect process or material. Let's assume that our bad parts will have readings from 5-10 lbs so we will ensure that all of them are bad parts of the same lot. We can start the first trial using a good part in the first sample, then we will use a bad part for the 2nd sample, a good part for the 3rd sample, and so on, until completion of the first trial. The second and 3rd trial will have the same criteria as the first trial. The second operator will repeat the same steps until completion of all samples. You will note that the resulting GR&R variation will be less than 20% so the GR%R may be acceptable. You can use the same approach with almost every destructive test.