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I’ve written a lot about how to evaluate the uncertainty measurements. My articles have ranged from basic introductions to metrology and uncertainty budgets, to more advanced topics such as sensitivity coefficients and Monte Carlo simulation. To date, all of the examples I’ve used have been for variable gauges. These are measurement instruments that give a numerical measurement result, on a scale, dial or digital display.
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Best explanation I have seen yet
This is the best explanation I have seen so far of attribute gage R&R. It shows that, even though the attribute gage returns only pass/fail data, if one measures the same part (or known standard) enough times, it is possible to get a percentage of items that pass in each case, and use the normal distribution to estimate the gage's mean and also its standard deviation.
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