Gage R&R Destructive Testing


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AIAG Gage R&R Destructive Testing

What can you do when each piece is destroyed when measured during a Gage R&R study? What if you conduct an impact or other test that makes it impossible to measure repeatedly? Let's look at using an XmR chart.

In this example, there were 10 testers destructively testing 10 samples each from the same production lot. The lower specification limit is 16.7 foot pounds/sq in.

If we put a blank row between each of the 10 testers data and run the XmR chart, we get an average and range that look like this:

If all 10 are using the same process to measure samples from a well-known and established process, then we'd expect the averages to be the same and the variation represented by the UCL and LCL to be equal.

If the averages or standard deviations are different from appraiser to appraiser (i.e., tech to tech), then the measurement system needs improvement.

Look at the X chart. Six of the ten share roughly the same average and the last three share a different average. If they are all measuring samples from the same lot, then they must be using two different measurement processes. Tech 7 is between the other two groups. Which of the two main groups are measuring correctly? How can you train the others to match?

Look at the X chart and the R chart to evaluate the variation (another key factor in Gage R&R).

Technician four, six, and ten have the least variation. What are they doing that produces more consistent results? How can you train the others to match the consistency?

Ideally, all of the appraisers should get close to the same average and standard deviation. Adjust the measurement process until you get the UCL, LCL, and CL to line up more closely.

AIAG Measurement System Analysis Gage R&R Overview

Gage R&R Bias and Linearity

AIAG Case Study - Non-replicable

Gage R&R Software
Obviously, crunching all of the numbers for a Gage R&R study is non-trivial, but you can do it easily with the Gage R&R template for Excel. Buy one separately or as part of the QI Macros for Excel SPC Software.

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