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2. Measurement Process Characterization
2.2. Statistical control of a measurement process


What are the issues in controlling the measurement process?

Purpose is to guarantee the 'goodness' of measurement results The purpose of statistical control is to guarantee the 'goodness' of measurement results within predictable limits and to validate the statement of uncertainty of the measurement result.

Statistical control methods can be used to test the measurement process for change with respect to bias and variability from its historical levels. However, if the measurement process is improperly specified or calibrated, then the control procedures can only guarantee comparability among measurements.

Assumption of normality is not stringent The assumptions that relate to measurement processes apply to statistical control; namely that the errors of measurement are uncorrelated over time and come from a population with a single distribution. The tests for control depend on the assumption that the underlying distribution is normal (Gaussian), but the test procedures are robust to slight departures from normality. Practically speaking, all that is required is that the distribution of measurements be bell-shaped and symmetric.
Check standard is mechanism for controlling the process Measurements on a check standard provide the mechanism for controlling the measurement process.

Measurements on the check standard should produce identical results except for the effect of random errors, and tests for control are basically tests of whether or not the random errors from the process continue to be drawn from the same statistical distribution as the historical data on the check standard.

Changes that can be monitored and tested with the check standard database are:

  1. Changes in bias and long-term variability
  2. Changes in instrument precision or short-term variability
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