Gage Error vs. Dimensional Tolerance - Accuracy needed for measurement equipment

I

inspector G

#1
I have a question about what is the correct accuracy needed for dimensional measuring equipment in relation to the dimensional tolerance of the characteristic being measured. Is there a document that I could refer to for guidance. I need to justify the costs related to a 10% product tolerance rule currently used to select measuring equipment accuracy. I am mostly dealing with CMM's and micrometers.

Thanks for any guidance
 
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Jerry Eldred

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#2
I'm not the expert in this specific detail. But I'll try to shed a little light that I hope may be of some help. The 10% ratio (after a little web research) relates to a Six Sigma term, "Precision To Tolerance Ratio". If you look that term up in google or some search engine you'll find quite a bit.

Again, not as an expert, I found some postings on a website called www.isixsigma.com.

Your justification may come from either Six Sigma documents, Measurement Systems Analysis documents or Gage R&R documents, which say that in order to statistically discern if you meet a given tolerance, you need precision / resolution at least 10 times greater.

Maybe one of the statistics folks can add something, or you could post something in one of those sections of this forum.
 
B

brobinson

#4
Where I work this is what is stated in our ISO 9001:

1. Measurement uncertainty for M & ME will not exceed one-fourth of the product tolerance. As an example, if the measurement uncertainty of a measuring instrument was +/-.0003, it would not be permissible to use this instrument when measuring a product with a tolerance less than .0012.


2. The calibration device used to check the above instrument shall also have a measurement uncertainty no greater than one-fourth of the M & ME measurement uncertainty. The calibration device must have a measurement uncertainty no greater than .000075 or one-fourth of .0003.


3. In some cases, even though the M & ME measurement uncertainty is no greater than one-fourth of the product tolerance, it is possible the product could be out of tolerance. Problems caused by instances such as this will be reviewed through statistical methods at the monthly meetings of the Corrective Action Review Board. If the CARB suspects a possible capability problem with a measuring instrument, Quality Control will conduct a gauge repeatability and reproducibility study. The findings will be presented to the CARB at the next meeting for disposition.
 

bobdoering

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#6
You may find the Gage R & R procedures in the AIAG Measurement System Analysis (MSA) book handy, too. Some folks may dispute the details, but the basic concepts are a very good starting point.

http://global.ihs.com/search_res.cfm?MID=W097&input_doc_number=AIAG%20MSA

If you are doing statistical process control, your statistical resolution should be 10% of the control limit range. That is an easier on to explain - it means that you have 10 statistically discreet intervals - 5 above the mean, 5 below. Less than that is far too insignificant for SPC. :cool:
 
M

Murphys Law

#7
My head hurts on this but my rule of thumb is to overlay the error of measurement on the range of the readings themselves.

If the minimum readings or maximum readings in a sample are towards spec limits, ask yourself the probability that you are accepting false passes.

If they are very close, you are in risk of getting out of spec material.

If distribution is far from it, then probably not it is not a concern. But if readings are very close too your limit with a uncertainty on the reading, then require a second sampling with increased sample size to validate the uncertainty error is not an issue. If you find your distribution is within this grey area, then 100% inspect.

This will also depend on whether your parameter is critical or not.

10% GR&R is actually pretty good. 10% tolerence isn't so.
 

bobdoering

Stop X-bar/R Madness!!
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#8
My head hurts on this but my rule of thumb is to overlay the error of measurement on the range of the readings themselves.

If the minimum readings or maximum readings in a sample are towards spec limits, ask yourself the probability that you are accepting false passes.

If they are very close, you are in risk of getting out of spec material.

If distribution is far from it, then probably not it is not a concern. But if readings are very close too your limit with a uncertainty on the reading, then require a second sampling with increased sample size to validate the uncertainty error is not an issue. If you find your distribution is within this grey area, then 100% inspect.
This is a great point - when you start to overlay the gage error (how close to the true measurement?) with the sampling error (what are the parts I didn't measure really like?) they gray area can get pretty big. More samples helps, but only 100% inspection eliminates that error and leaves you with the measurement error. Do you really want to go there? So, the better the gaging the closer you can get before you have to deal with that. Both great reasons why production should never run to the specifications on the floor. Tough to convince the operations people of that, though (You are taking away from my tolerance! Well, yes, but you never really had it.):cool:
 
M

MIRCS

#9
I've always used the 4:1 ratio. Having the standard four times better than what you're testing. They call for a 10:1 in some document somewhere, but in time the difference is negligible using a 4:1.

The main problem that many people are starting to face is that a 4:1 is getting harder and harder to maintain as equipment gets more accurate.
 
I

inspector G

#10
Thanks for the reply. I would like to inquire about your reason(s) as to why 10% of GR&R is ok but using 10% of the dimensional tolerance is not an acceptable critera for gaging accuracy?
 
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