Gage R&R study questions answered

August 4, 2010
2 min read
General

We frequently entertain questions about MSA and specifically, gage R&R. Below are two questions we recently received:

Question #1: “What are the requirements for the parts chosen in a study? Do the parts have to have the same specification?”

Answer: The parts selected should be representative of the process variation that is producing them. This implies that selecting 10 consecutive pieces (parts) is not as good as using 10 parts obtained throughout the day or week. Part of what you are trying to do with an R&R study is determine whether your measurement system is capable of distinguishing parts made on the same process to the same specification. In summary, you want to select the parts in a way that represents the minimum sized part, the maximum sized part and those in between. If the selected parts have different specifications, they are different by design, not by random variation.

Question #2: “Results can be calculated in several ways: using study parameters, specifications and others. Which is most acceptable for gage R&R?”

Answer: The industry trend is to use study/process parameters, however, how you calculate the results of a gage R&R study depends on the purpose for doing the study. Before the study begins, you should decide what the primary purpose for conducting the study is. If you are trying to control your process, you need to be able to detect changes in the process. To do this, you should use study parameters or process parameters. If your focus is being able to compare a part to specifications, then you should use the specification method. Using the specification method suggests that you are trying to prove that your measurement system can distinguish between good and bad parts.

If you have any other questions or concerns about MSA or gage R&R, please contact us at [email protected] or by phone at 800-777-5060 or just post them below.

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Grace Barton

Marketing Specialist

Grace Barton is a digital marketing and competitive intelligence professional who crafts strategic narratives by bridging marketing insights with analytical expertise. At Advantive, she creates engaging, data-driven content tailored to the distribution, manufacturing, packaging, and quality industries. Her goal is to deliver impactful messaging that drives engagement and growth based on specific gap closure needs, whether responding to sales organization requirements, pinpointing gaps in content, or meeting immediate market trends.
She thrives on transforming competitive intelligence into actionable insights for the sales organization. Grace manages Advantive's competitive intelligence platform, Klue, to equip the sales team with the battlecards and market data they need to stay ahead of competitors. Since launch, she's built 28+ battlecards across four lines of business, ensuring the GTM strategy stays sharp.
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Areas of Expertise: Digital Marketing, Competitive Intelligence, Strategic Narratives, Marketing Insights, Analytical Expertise
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