This is the fourth in a series of articles about MSA. The focus of this article will be on measurement stability.

Stability is simply measurement bias throughout an extended period of time. This is where calibration falls short from an MSA perspective. Calibration is a series of snapshots widely spaced in time taken under controlled environmental conditions. A stability study is a series of repeated measurements taken under actual usage conditions. The purpose is to verify that the bias of the gage does not change over time due to environmental conditions or other causes.

A stability study is performed by selecting a measurement standard (ideal) or a master sample part that is midrange of the expected measurement range. Note: This may be enhanced by adding standards/master parts at the low and high ends of the expected measurement range. On a periodic basis, measure the standard 3 – 5 times. The period should be based on knowledge of what may influence the measurement system. For example, if ambient temperature variation is expected to be the major source of variation, make hourly checks throughout the day. If the source of variation is expected to be long term drift, take daily or weekly measurements.

Analyze the data using Xbar/R or Xbar/s control charts (use separate charts if you measured at the low/middle/high ends of the expected measurement range). The subgroups are comprised of the 3 -5 measurements and measure short term repeatability of the measurement device. If the control chart is in a state of statistical control throughout the study period, the gage stability is acceptable. There is no numerical acceptance criterion. If the control chart is out of control, analyze the patterns.

The next article will be:

Stability is simply measurement bias throughout an extended period of time. This is where calibration falls short from an MSA perspective. Calibration is a series of snapshots widely spaced in time taken under controlled environmental conditions. A stability study is a series of repeated measurements taken under actual usage conditions. The purpose is to verify that the bias of the gage does not change over time due to environmental conditions or other causes.

A stability study is performed by selecting a measurement standard (ideal) or a master sample part that is midrange of the expected measurement range. Note: This may be enhanced by adding standards/master parts at the low and high ends of the expected measurement range. On a periodic basis, measure the standard 3 – 5 times. The period should be based on knowledge of what may influence the measurement system. For example, if ambient temperature variation is expected to be the major source of variation, make hourly checks throughout the day. If the source of variation is expected to be long term drift, take daily or weekly measurements.

Analyze the data using Xbar/R or Xbar/s control charts (use separate charts if you measured at the low/middle/high ends of the expected measurement range). The subgroups are comprised of the 3 -5 measurements and measure short term repeatability of the measurement device. If the control chart is in a state of statistical control throughout the study period, the gage stability is acceptable. There is no numerical acceptance criterion. If the control chart is out of control, analyze the patterns.

- For example, the influence of temperature would be expected to appear as cyclical trends that coincides with the ambient temperature.
- If the gage operates on plant utilities (e.g., air pressure) abrupt shifts could occur based on plant demand on the utilities (e.g., air pressure).
- Single points out of control could be the result of a gage that is overly sensitive to operator technique.
- Runs could be the result of different measurement methods

The next article will be:

**Intro to Measurement System Analysis (MSA) of Continuous Data – Part 5: Repeatability & Reproducibility**
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