Correct Sample Size for Attribute Gage R&R (Good / Bad parts)

L

liamtek

#1
Hi to all,
Could someone help me to confirm the correct/estimated sample size used to do an Attribute GR&R?, this means, how many good / bad parts are needed?.

We need to develop an Attribute GR&R for an AOI (Automatic Optical Inspection).

Hope you can help.
Thanks
 
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Jim G

Involved In Discussions
#3
A common standard for a Continuous GR&R study is to use 10 parts, measured by 3 different people, 3 times each, giving you a total of 90 results.
For Attribute data GR&R studies more data is required (Due to Attribute data having less resolution) therefore at least 20 parts should be assessed at least 3 times by each appraiser giving 180 results.
You should also ensure your selection of parts includes some borderline products to challenge the abilitiy of the measurement system.
Hope this helps
Jim G

We learn more by looking for the answer to a question and not finding it than we do from learning the answer itself.--Lloyd Alexander
 

Bev D

Heretical Statistician
Staff member
Super Moderator
#4
there are a couple of approaches for sample size that work for attribute (aka categorical) data guage R&R studies. The best approach is dependent on what you are trying to accomplish with the study.

Check out this attachement which details these approaches and the appropriate statistical analyses... Categorical Data MSA

...for what it's worth - I dont' recommend 'reading' each unti three times. twice is sufficient and ti allows you to increase your sampel size appropriately without increasing the amount of work the subjects have to do. This is particularly true for categorical data as most of the appropriate statistical tests are based on two readings for each unit and tehy get very complicated very fast when you increase the number of readings - without a corresponding increase in the usefulness of the data results.

Remember that a R&R study is trying to determine the measurement error, which is expressed in terms of the standard deviation. This standard deviation is from teh repeated measurements of a single unit. the improvement in the SD estimate of a sample of 2 to a sample size of 3 is negligable. However, increasing your unit sample size from 10 to 30 has a significant improvemetn in the estimate of the measurement error by virtue of using 30 sample SDs instead of 10 sample SDs...
 
L

liamtek

#5
All the info you provided is good, but nobody answer my question, I will try to explain in a another way.

What I want to know is how many parts (good & Bad) I need in order to do an attribute GR&R?

Example:

I need to do a GR&R in the Automatic optical Inspection (AOI), this equipment is detecting the lack of electrical components, in order to do the GR&R, what is the standard quantity of good pcs & the standard quantity of bad pcs in order to do the GR&R, for example if we use 30 parts, how many parts needs to be good & how many neds to be bad parts?

Currently I'm selecting between 20 to 30 test samples that represent the full range of variation encountered in actual production runs. For maximum confidence, I'm using a 50-50 mix of good/bad parts but also a 30:70 ratio is acceptable. But I'm doing this according to my experience, but I need to know if there is something in a procedure, MSA, Customer requirements in order to ensure I'm following a standard sample.

Please advise, any comments are very welcome....
 

Bev D

Heretical Statistician
Staff member
Super Moderator
#6
How many parts needs to be good & how many neds to be bad parts?

Currently I'm selecting between 20 to 30 test samples that represent the full range of variation encountered in actual production runs. For maximum confidence, I'm using a 50-50 mix of good/bad parts but also a 30:70 ratio is acceptable. But I'm doing this according to my experience, but I need to know if there is something in a procedure, MSA, Customer requirements in order to ensure I'm following a standard sample.

Please advise, any comments are very welcome....
Sorry to respond so late -I got distracted.

There is no published 'valid' standard other than if you go to the formulas that calculate the statistical significance of 'disagreement' given a sample size. but this is probably far too complicated for what you are trying to do.

I have two basic approaches:

first I use a roughly 50:50 split with an over sampling of 'marginal' parts to test the instruments ability to discriminate in the marginal zone. (this is only diagnostic in helping me improve the discrimination IF I need it.) from this you could calcualte your false accept/reject rates IF you know the distribution of marginal devices to fully bad and fully good.

then I use a good:bad ratio that matches my current process, this way I can verify how many false rejections and false acceptances I will actually get. (this is the real purpose of the equipment...) This drives my sample size.
 

Englishman Abroad

Involved In Discussions
#7
All,

In the recently published Ford PPAP specifics there are some requirements for this;

Parts for Attribute Gauge R&R Study



25% of the parts should be near the lower specification limit (on both sides of the specification).




25% of the parts should be near the upper specification limit (on both sides of the specification).




30% of the parts should represent the expected process variation.




10% of the parts should be outside the upper gauge specification limit and beyond the 25% of the parts near the specification as described above.




10% of the parts should be outside the lower gauge specification limit and beyond the 25% of the parts near the specification as described above.


There is also a graph showing the distribution of these parts;



(See the IATF website Ford Customer Specific Requirements for PPAP, June 2013; Page 6 - sorry the web link was deleted)



Although only required by Ford, this provides good guidance for other customers in this complicated area.





 
Last edited:

Bev D

Heretical Statistician
Staff member
Super Moderator
#8
While this provides some guidance it is not based on any statistical theory, or performance requirement ()false rejection or false acceptance). It is a generic test but the results may be meaningless depending on teh actual defect rate and the required accept/reject rate.
 

michellemmm

Quest For Quality
#10
Hi to all,
Could someone help me to confirm the correct/estimated sample size used to do an Attribute GR&R?, this means, how many good / bad parts are needed?.

We need to develop an Attribute GR&R for an AOI (Automatic Optical Inspection).

Hope you can help.
Thanks
I have numerous questions:
1- Why would you need to perform GR&R on an AOI equipment?
2- Do you have other alternatives than manual inspection or ICT?
ICT does not help in terms of component orientation or polarity. And if you don't have 100% coverage, you will have other problems....
3- Do you have several AOIs or just one?
4- What are you trying to determine/accomplish?
5- How old is your AOI?
6- How do you calibrate your AOI?
7- What are you going to do with the data?

Personally, the last thing I would do is GR&R on AOI.
 
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