The World of Gage R&R (Repeatability & Reproducibility)

Introduction
The most complicated thing to understand in any process is ‘variation’ as with variation there are possibilities of uncertainty to be carried in processes. The more the variation, the more uncertain is any process.
In engineering and in contemporary administrative practices, the emphasis lies on minimizing variation. For such reason, initiatives are taken to design effective measurement systems that could possibly detect and reduce variation to maximum. Gage repeatability and reproducibility is one of such initiatives, a study that measures variation of a measurement system effectively. If a measuring system is corrected; reduced with variation, it possibly could minimize variation in actual process.
We are discussing here Gage R & R study, what is it and how it comes useful in designing effective measurement systems. It is to illustrate a step by step guide describing Gage R & R with meaning and purpose.

Defining Gage R & R
Gage Repeatability and Reproducibility is referred to a statistical tool that accounts variability of a measurement system. It measures variation that could possibly affect actual process outcome. Gage R & R investigates several exposed factors causing variation. Fundamentally it focuses on two types of variations, repeatability and reproducibility.
Let’s consider example of three inspectors who are inspecting size of a bolt. If their values come similar at first take, they are repeatable in their results. Similarly, if there values remain coherent even in three takes, they are reproducible. Gage R & R mainly focuses on these two types of variability in order to bring understanding of actual variation if existed in a measurement system. By this, Gage R & R actually checks precision and how much accurate a measuring system is for bringing desired results and function.

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Gage R & R and Acceptability
1. Components Variance
If a measurement system components vary less than 1 % it is a more acceptable system according to Automotive Industry Action Group (AIAG) guidelines. If components variance is beyond 9%, the system needs to be assessed and changed with its flawed components. Error free components are more essential for Gage R & R study, which assures instant change of components that carry flaws or some sort of error. Errors cause variance and variance affects process outcome. So variance needs to be tackled at each stage of measurement system.

2. Process Variance
In contemporary practice, Gage R & R measures acceptability of apparatus to get it approved for use and function. If percentage of variation is less than 10%, it is an acceptable system according to AIAG standards. If process variation goes beyond 30%, the apparatus needs to be changed or replaced if could not be fully repaired. It is an expensive activity to replace the whole system, but it is done to assure all sorts of variance is gone from the measurement system. The more improved is the measurement system, the better and improved is the actual process outcome.

Considerations and Procedure of Gage R & R
There are mainly two considerations in a Gage R & R study, to assess part-to-part variation and variation of measurement system. With this the Gage R & R tells either the measurement system dominates part-to-part variation, accurately discriminates between parts. Consistency of measurement system is most important in Gage R & R conduct.

Gage R & R focuses on obtaining certain indications from it’s conduct. Firstly, Gage R & R makes sure that measurement system varies lesser compare to variation of actual process. The study affirms that system error is reduced to minimum as compare to human error which is natural during conduct of study. Thirdly, it makes sure that all sources of variation becomes avoidable in order to ensure precision and accuracy.
The primary sources of data are used in Gage R & R conduct. A quantitative analysis is done to achieve desired inputs in the study. Interpretation of results is made using ANOVA and Gage R & R table. Gage R & R ends up reducing variation to minimal.

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