Monitoring Gauge Accuracy throughout the year using SPC

Miner

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#11
bmccabe said:
:applause: Very good observation. :applause:

I have looked at, and devised many tests, to quantify the influence of form errors to measurement data and R&R analysis. What you and I know, but have yet stated, a GR&R will not attribute form error to part variation. When encountered, form error will be assigned to equipment variation (most likely) or operator influences.
Correct. If it is significant, you try to minimize the effect through consistent fixturing, or subtracting the variance from the MSA variance.

bmccabe said:
:This however was not the case with the data collected. The pin was not moved throughout the entire run: The program was set to auto-cycle, and produced a new data set every 40 or so seconds. What you are seeing in the data is the resolution and accuracy of the equipment only (by the design of data collection, not voodoo arithmetic.)

The cyclic behavior in the data is normal for these types of things. It's cause could be changes in dew point (the room is fairly temperature controlled, but relative humidity does change some.) It could be caused by changes in ambient light, or external vibrations, or even phase variations in the electric supply. Who knows... It's under a micron! ...Who cares!!!
After rethinking the periodicity of the data, I agree that it is probably in the machine itself or the environment. Try subgrouping the data (XBar/R) and spacing the time between subgroups such that the period effect is randomized. You should end up with an in-control XBar/R chart with limits close to the manufacturer's stated accuracy.
 
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bmccabe - 2006

#12
Well, that definitely opened the control limits.
We are still about half the stated accuracy
(or my ability to care about improving).

Still, that’s a good point: Randomizing the data will open control limits.
Another question, if you’d care to answer. Do we want to randomize serial data? – Ever?
I’m sure the stats cops here will start whooping and swinging from the trees if we do.
 

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Miner

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#13
I wasn't clear enough. Do not randomize the data.

Use the data that you have already collected.

Pick a subgroup size. For the sake of clarity, I will use n=5. Take the first 5 data points, calculate average and range.

Pick a sampling interval. Again, for the sake of the example, use 30 minutes. Ignore the data points you collected between the first subgroup and the first reading at t=30 minutes. Take the next 5 data points, calculate average and range and repeat at 30 minute intervals until you run out of data.

Use these subgroups to create an XBar/R chart (not I-MR) in actual time sequence. Since the sampling frequency is significantly greater than the period shown in your data set, your subgroups should be taken when the "sine wave" is at a random amplitude. This will eliminate the pattern from your chart.

If the limits are still not quite right, there is a possibility that some degree of autocorrelation exists between successive data point for a small time interval. You could take every second or third data point when creating a subgroup as a test.
 
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