Last Updated on 16 September 2023
The R&R part of the name stands for ‘Repeatability and Reproducability’.
- Repeatability = Equipment Variation (EV) or variation due to changing the measurement equipment but keeping the appraiser the same. Call the appraiser ‘Pete’ if it helps you remember the name ‘Re-Pete-ability’.
- Reproducability = Appraisal Variation (AV) or variation from changing the appraiser but keeping the measurement instrument the same.
Reliable data is the lifeblood of any Six Sigma project. The power of Gage R&R stems from its ability to ascertain the precision of the measurement system, enhancing the credibility of your data. Let’s examine how refining your Gage R&R skills can boost your Six Sigma prowess.
1. Data Accuracy
The first ‘R’ in Gage R&R stands for Repeatability, which is the variation in measurements taken by a single person or instrument on the same item and under the same conditions. Imperfect accuracy could introduce errors in your data, which could potentially derail your Six Sigma project.
2. Data Consistency
The second ‘R’ stands for Reproducibility, signifying the variation observed when different operators measure the same characteristic on the same part. Variances in data consistency can lead to misleading results, impacting the success of your Six Sigma project.
3. Effective Decision Making
Mastering Gage R&R augments the decision-making process. As a Six Sigma practitioner, you understand the importance of-informed decisions based on accurate and reliable data. An effective Gage R&R analysis ensures that the data you leverage for your projects is free from measurement system errors.
Practical Steps towards Gage R&R Mastery
Understanding the theoretical aspects of Gage R&R is just the beginning. Practical application is where you truly hone your skills.
1. Understand the System:
Before you measure, understand the system, including the people (who is measuring), the methods (how they are measuring), and the instruments (what tools are being used).
2. Plan Your Study:
Decide what will be measured, who will measure it, and under what conditions. Also, decide on the appropriate statistical methods to analyze the data.
3. Execute Your Study:
Train your team to measure in a similar way by conducting pilot studies. Finally, execute your plan, ensuring to capture pertinent circumstances that might impact your data.
4. Analyze Data:
Use statistical software to analyze your findings, paying attention to both repeatability and reproducibility variations.
Take steps to reduce variations wherever possible through continuous improvements – the Kaizen way.