Key takeaways
  • Measurement System Analysis asks how much of your observed variation comes from the measurement rather than the product.
  • Repeatability is one person measuring the same part twice. Reproducibility is two people measuring the same part.
  • Under 10% of total variation is generally acceptable, 10 to 30% is conditional, above 30% means your data is largely measurement noise.
Why this comes first
You cannot improve what you cannot measure reliably

A capability study, an SPC chart and a scrap analysis all assume the measurement is trustworthy. If a third of the observed variation is the gauge, every conclusion drawn from that data is partly fiction.

What the two Rs mean

  • Repeatability. Equipment variation. The same operator, the same part, the same gauge, measured again. Spread here is the instrument.
  • Reproducibility. Appraiser variation. Different operators measuring the same part. Spread here is technique, fixturing or interpretation.

Running a study

  • Select around ten parts that span the range of variation you actually see, not ten good ones.
  • Use two or three operators who genuinely do this measurement.
  • Each measures every part two or three times, in random order, without seeing previous results.
  • Label parts so operators cannot identify them, or you measure their memory.
  • Analyse to separate part variation, repeatability and reproducibility.

Reading the result

  • Under 10% of total variation: acceptable.
  • 10 to 30%: may be acceptable depending on the importance of the characteristic and the cost of improving it.
  • Over 30%: the measurement system needs work before the data is used for decisions.
  • Also check the number of distinct categories, which should be five or more; fewer means the gauge cannot really tell parts apart.

When the result is poor

Look at which component dominates. High repeatability variation points at the instrument or the fixturing: worn gauge, unstable setup, insufficient resolution. High reproducibility points at method: operators locating the part differently, applying different pressure, or interpreting an ambiguous instruction differently. The second is usually cheaper to fix, through a written method and a fixture.

Attribute measurement

For pass and fail judgements, run an attribute agreement analysis instead: several appraisers judging the same set of borderline items twice, compared against a known correct answer. Disagreement on visual standards is extremely common and is usually solved with boundary samples rather than more training.