How should I analyze measurement correlation between me and customer?

QE1993

Involved In Discussions
#1
We have to do this in a pinch, so we don't have a large sample size to work with.

We measured 21 parts and they measured the same 21 parts.

Now, I"m unsure what to do with this data.

Normally, I would put something like this into an expanded GR&R study, but I'm not sure that we have enough data points for that to be representative.

I've tried finding the correlation coefficient between the 2 sets of data, but have no idea what the threshold for that is. I know it should be close to 1, but how close? I also don' t know if this is the appropriate stat.

Any suggestions?
 
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Ninja

Looking for Reality
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#3
FWIW, I've often simply sent the data to the customer with a nice note saying, "Looks great to me, please confirm".
Don't let the data cover over the purpose...
 

Ninja

Looking for Reality
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#5
LOL...I thought of that right as I hit the "post reply" button...

In that case, I would call the customer and discuss the data and collection technique...same as if the customer took a look at what I sent and replied "no, it doesn't look adequate".

Either way, it is the customer handling the data that generates approval, not my handling of it...I guess that was the point of my post.
Thanks for calling me on it.
 

Welshwizard

Involved In Discussions
#6
You measure 21 parts and your customer measures 21 parts. You hint at normally using GRR so that implies that you have measured the 21 parts with multiple people or some other level.
As you wish to compare against your customer, they must also carry out the same process and procedure otherwise any comparisons are nonsense. In particular, the achievement identified in step 3 is critical.
The process I describe is an alternative to GRR which could also be performed, it would however take a long time to complete for the 21 parts although it would also be possible to substitute the estimate for part variation of the 21 parts into a GRR study.

1.
I would select one of your parts and measure it at least 20 times using your most familiar operator over an appropriate time frame to expose any sources of variation.
2.
I would arrange the data in time series order and plot them on an individual moving range chart. Any points outside the control limits will indicate a lack of measurement consistency which would need to be formally addressed before carrying out further studies. Assuming consistency...
3.
Repeat the study for all the operators or levels carrying out steps 1 and 2.
At this point you should have demonstrable measurement consistency for all your operators/levels, this is a major achievement on its own but we can then go on if necessary
4. Check for equivalence of measurement error and bias, either between the operators/levels or to a known standard as applicable
5. Select any of the operators and measure the 21 parts, plot the values in time series order on an individual moving range chart. Extract the part variation from this chart and compare with the measurement error plus any detectible bias (if its detectible)) to compute the Intraclass Correlation.

Following all this you can demonstrate to your customer:
-The measurement process is consistent across all the operators/levels
-The measurement error is equivalent (if not I have documented it and understood the possible impact)
-The bias is equivalent (if not I have documented it and understood the possible impact)
-The measurement process is capable, or not as the case may be, of picking up and tracking variation in my manufacturing process

At this point you are then in a strong position to compare against your customer measurements and ask questions. Perhaps your customer would not then feel the need to check your measurements, a time saving for you both.?

I hope this helps.For more detail on equivalence please look at Don Wheeler's 3 recent articles published on Quality Digest.

Cheers
 
Last edited:

Mike S.

Happy to be Alive
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#7
you can simply plot the data on a youden plot and calculate the intraclass correlation coefficient. a standard correlation is not appropriate.
you can check out the two attachments for background.
You did a LOT of work creating all this. I'd like to sit in on one of your presentations but I may leave with a headache. "Fake math" - love the term, BTW. (y)
 

Emmyd

Involved In Discussions
#9
You and your customer are using the same measurement method?
That would be my question as well. We've done this exercise with our customers before only to find they were using a different method of measurement/datuming/clamping than what was approved on the gauging. We had to make sure the measurement methods are exactly the same or you can't correlate anything.
 

Bev D

Heretical Statistician
Staff member
Super Moderator
#10
You did a LOT of work creating all this. I'd like to sit in on one of your presentations but I may leave with a headache. "Fake math" - love the term, BTW. (y)
I usually present at the ASQ Lean Six Sigma conference in Phoenix and I might be presenting at the ASQ world conference in Columbus next year. My presentations are typically fairly 'rich' in content and I do tend to challenge popular 'thinking' ;)
 
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