How to conduct R&R Study for Runout Measurement & for unilateral toleranced features

Can any one suggest us how to conduct Gage Repeatability and Reproducibility for RUN OUT measurement with Lever Dial of 0.001mm Least Count. Acceptable limit of Run out is 0.05mm. Whether we can fallow same method as reference in MSA manual of QS9000 as run out checking is with single sided tolerance.

First, is there a special Gage R&R method for unilateral toleranced features? No. The methods are the same, but the interpretation of the data must be treated differently. "Unilateral features may produce "bounded data". Basically, that is any measurement data limited by an upper or lower value (e.g. runout, flatness, straightness, etc. where measurement values cannot be recorded lower than "0"). For example, a highly capable process could produce a diameter with a runout tolerance of .001" max that measures on the average .0002" with occasional measurement values up to .0012". This would be considered a capable process. If we tested the data it would not be normal (bell shaped curve)but appear skewed right.
When we violate the assumptions of any statistical tool, the tool becomes unpredictable and may indicate a false conclusion. What happens to unilateral data that is not normal, but treated or assumed to be normal? The measurement system appears unstable, the Gage R&R error is inflated. It makes the measurement system look worse than it is.
An advanced practitioner of GR&R understands the assumptions of the tool and remains a healthy skeptic (test the assumption). When you know that you are dealing with unilateral or skewed data - test it for normality. If it is normal data, proceed with the standard methods and evaluation techniques. If the data is not normal, you can usually transform it to act normal, then proceed evaluating the transformed data. If you can't transform, proceed with skeptic caution. You will rely on profound knowledge an practical experience with the measurement system.
Certain high-end measurement systems (circular geometry, surface finish, CMM, etc.) are best evaluated using a control chart method and measuring master artifacts on a regular schedule.

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Dave S.

[AJLenarz]

I don’t consider myself a MSA guru, but I have been practicing R&R’s now for about 10 years. I must admit, Mr. Stauffer’s previous post made me go back and review the MSA manual. I would like to pose the question, where in the MSA manual does it state that the process must be in statistical control? What relevance is it if the process is yielding a skewed bell curve? The MSA manual does state, “The measurement system must be in statistical control. This means that the variation in the measurement system is due to common causes only and not due to special causes.” Also that data is reviewed to determine “statistical control with respect to repeatability”. But I don’t see where it relates back to process control. Please enlighten me.

If you refer the Section 4 General Guidelines of MSA Manual, The assessment of the measurement system is done in two ways, Phase 1 and Phase 2.
The purpose of Phase 1 is to find the measuring system possess the statisitical properties. If the measuring system is running with Special causes, we cannot predict the system performance over a period of time. Hence, its must we should assess the measuring system is possess appropriate statistical properties.
Phase 2 is done to continously ensure the system is under statiscal (ie., only with common cause), one form of phase 2 testing is commonly by Gage R&R.

[AJLenarz]

I believe I agree. But let me see if I understand this correctly. Phase 1 is broke up into two parts. The first section of phase 1 is to determine if the measurement system possesses the required statistical properties or not. These statistical properties include the determination of adequate discrimination, system stability over time and linearity (among others). The second part of phase 1 is to determine if environmental factors have a significant influence on the measurement system.

Phase 2 in a nut shell is GR&R process.

Now, I am still a little bit fuzzy on how a process (such as the one in second post) with a skewed bell curve could make “the measurement system appears unstable” and the “gage R&R error is inflated”

I always thought the GR&R study was independent of the (manufacturing) process distribution. Process spread is different; the GR&R result will be impacted by the spread of the process if the samples collected represent the entire process range. But what impact will it have on a GR&R study if the manufacturing process has a skewed bell curve or not?

But like I have said before, I am still a young buck in the world of quality with a lot to learn.