Measurement Systems Analysis and Gage R&R for the CQE
If you cannot trust your measurements, you cannot trust any decision built on them. Here is how MSA and Gage R&R keep your data honest.
Every number a quality engineer acts on comes from a measurement, and every measurement contains error. Before you trust a control chart, a capability index, or an acceptance decision, you have to know whether your measurement system is telling the truth. That is the job of measurement systems analysis, and it is a reliably tested corner of the CQE Body of Knowledge.
I am John Lee of Alpha Training and Consulting. This guide explains the components of measurement error and how a Gage R&R study quantifies them.
Why measurement error is dangerous
The total variation you observe is a combination of true process variation and measurement system variation. If the measurement system contributes a large share, it can disguise a good process as bad or pass a bad process as good. Because measurement error is baked into every downstream analysis, validating the measurement system comes before validating the process.
Gage R&R: repeatability and reproducibility
A Gage R&R study decomposes measurement variation into two parts. Repeatability is the variation you get when one appraiser measures the same part repeatedly with the same instrument—it reflects the equipment itself. Reproducibility is the variation between different appraisers measuring the same parts—it reflects differences in technique, training, and interpretation. A typical study uses several parts, a few appraisers, and multiple trials each.
Bias, linearity, and stability
| Term | What it describes |
|---|---|
| Bias | The difference between the average measurement and the true (reference) value. |
| Linearity | How bias changes across the operating range of the instrument. |
| Stability | How the measurement system drifts over time. |
| Resolution | The smallest change the instrument can detect and display. |
Judging whether a measurement system is acceptable
The results of a Gage R&R are usually expressed as a percentage of either the study variation or the tolerance. Under 10 percent is excellent; 10 to 30 percent is conditionally acceptable, weighed against the cost and importance of the measurement; above 30 percent signals a measurement system that needs improvement before its data can be trusted. Another metric, the number of distinct categories (ndc), should generally be five or more.
Measurement systems analysis is the quiet prerequisite for almost everything else in quantitative methods. Validate the gage first, then interpret your control charts and capability indices with confidence.
Frequently asked questions
What is the difference between repeatability and reproducibility?+
Repeatability is the variation when the same person measures the same part with the same device multiple times—it reflects the equipment. Reproducibility is the variation between different appraisers measuring the same parts—it reflects the people and method.
Why does measurement error matter so much?+
Measurement error is confounded with process variation. If your gage is noisy, a capable process can look incapable and vice versa. Every decision built on the data—control charts, capability, acceptance—inherits that error.
What percentage of Gage R&R is acceptable?+
A common rule of thumb: under 10 percent of the study variation or tolerance is excellent, 10 to 30 percent may be acceptable depending on the application and cost, and over 30 percent is generally unacceptable.
Written by
John Lee
President, Alpha Training and Consulting
John Lee has more than 25 years of experience in quality engineering and has personally earned every ASQ certification, including the Certified Quality Engineer (CQE). A Shingo Award–winning author, he has helped thousands of engineers pass their ASQ exams on the first attempt with a 94% first-time pass rate.
Certifications: BSME, MBA, CMQ/OE, CQE, CRE, CQA, CQIA, CQI, CCT, CQPA, CQT, CHA, CBA, CSQE, CSQP, CCQM, CSSYB, CSSGB, CSSBB, CPGP, CMBB
Alpha Training and Consulting is an independent training provider and is not affiliated with, endorsed by, or sponsored by ASQ. "ASQ" and "Certified Quality Engineer (CQE)" are trademarks of the American Society for Quality. Exam policies, fees, and Body of Knowledge weightings are set by ASQ and can change—always confirm current details at asq.org.