Which practice quantifies measurement system variation and ensures consistent results in verification?

• A. Ignoring minor drift
• B. Periodic recalibration only when failed
• C. Apply Measurement Systems Analysis (MSA) to quantify variation
• D. Reducing sampling size

Answer: (C)

Measuring how much variation comes from the measurement process itself and making verification results reliable comes from using a formal Measurement Systems Analysis. MSA provides a structured way to quantify the variation introduced by the measurement system—things like the instrument, the operator, and the environment—separating that from the actual process being measured. By looking at repeatability (can the same setup produce the same result under the same conditions) and reproducibility (do different operators or conditions yield consistent results), MSA gives you concrete numbers such as gauge R&R that tell you how much of the observed variation comes from the measurement system and whether it’s within an acceptable range relative to tolerance. When the measurement system is shown to be stable and precise, verification results become trustworthy; if not, you can address issues through calibration, process improvements, or training. Ignoring drift, calibrating only after a failure, or reducing sampling size don’t systematically quantify or control this variation, so they don’t support reliable verification like MSA does.