Without quality, efficiency, and the right decisions, production environments cannot be strong. But how can you be sure that the data on which you base your decisions is actually reliable? The Gage R&R method is a useful tool for this. In this blog, we explain what Gage R&R is, how it is calculated, and the insights it provides.
What is Gage R&R?
Gage R&R stands for Gage Repeatability and Reproducibility. This statistical method is used within MSA (Measurement System Analysis). The purpose of Gage R&R within MSA is to assess the quality of a measurement system. In essence, Gage R&R helps determine whether measurement data is accurate enough to base decisions on. A measurement system does not consist solely of the measuring instrument. People, procedures, and the conditions under which measurements are taken also influence the measurement. Multiple factors can therefore affect the measurement outcome. Gage R&R allows you to analyze the extent to which measurement variation originates from the measurement system itself – and not from the product.
What do repeatability and reproducibility mean?
The R&R meaning can be reduced to two key concepts: repeatability and reproducibility. These two concepts play a central role in the Gage R&R method. Together, they provide a complete picture of how reliable a measurement system is. This works as follows:
- Repeatability: This refers to the extent to which the same evaluator, using the same measuring instrument, obtains the same results when measuring the same object multiple times. It provides insight into the reliability of the measuring instrument itself. For repeatability, it is important that the measurements are performed under exactly the same conditions multiple times.
- Reproducibility: This examines differences between evaluators. If multiple employees perform the same measurement using the same instrument, do they obtain the same result? This part of Gage R&R measures the variation that arises from the user of the system.
What is a good Gage R&R score?
The result of a measurement system analysis is usually expressed as a percentage of the total process variation. This percentage shows how much of the total variation is due to the measurement system itself. In practice, the following guidelines are often used for measurement system analysis percentages:
- 10% or lower: The measurement system is considered very good. The measurement results are reliable enough to base decisions on.
- 10% to 30%: The measurement system is acceptable, but improvement is definitely recommended. Whether this is sufficient often depends on the application.
- 30% or higher: The measurement data are unreliable. Such data can lead to incorrect conclusions, and the measurement system is considered insufficient.
How to calculate the R&R score
Repeatability and reproducibility together form the R&R. To calculate Gage R&R, multiple operators measure the same number of products a certain number of times. The results are then statistically analyzed, usually using ANOVA or the Range Method. A simple example:
- Three operators each measure the same set of 10 products 10 times.
- The differences within a single operator indicate repeatability.
- The differences between operators indicate reproducibility.
- Together, these two sources form the R&R score, expressed as a percentage of the total variation.
For example, if the total variation in a process is 100 units and the measurement system causes 12 units of variation, the R&R score is:
(12 ÷ 100) × 100% = 12%
This would fall into the ‘acceptable’ category, but there is still room for improvement.
Why is reliable continuous data important?
It is clear that reliable data is extremely important. Data forms the foundation of every improvement project and ensures that improvements have the desired effect. But what exactly is continuous data? Continuous data is a type of data that can take on any possible value. Continuous data is often measured using instruments such as a thermometer, calliper, or scale. The data can have infinitely many values within a specific interval. Examples include length, weight, temperature, time, pressure, or speed. In many cases, the measurements are not limited to whole numbers but extend into decimals. Continuous data is important for Gage R&R because it allows measurement variation to be analyzed with sufficient precision.
Gage R&R in the EZ-GO app
At EZ-Factory, we provide access to reliable data in a simple way. With the EZ-GO app, teams can digitally support and improve daily operations. You can track trends and deviations, link training and instructions to measurement procedures, and easily document and digitize standard work. By integrating Gage R&R with EZ-GO, teams can easily verify whether their measurement results are reliable.
Questions about Gage R&R or the EZ-GO platform?
Do you want to learn more about how to apply Gage R&R in your organization? Or are you curious how the EZ-GO app can help you ensure reliable data? Feel free to contact us. Our team is happy to assist and help you take the next step.