Gage R&R
Source:Var. Comp.Std. Dev.5.15*Sigma
Total Gage R&R104232.286166.27
Repeatability1042 32.286166.27
Part-to-Part145034380.8341961.29
Total Variation146077382.2001968.33
Source:%Contribution%Study Var.
Total Gage R&R0.718.45
Repeatability0.718.45
Part-to-Part99.2999.64
Total Variation100.00100.00
Number of Distinct Categories = 17
Gage R&R
–VarComp (or Variance)—the variance component contributed by each source.
–StdDev—the standard deviation for each variance component.
–5.15*Sigma—the standard deviations multiplied by 5.15. You can change the multiple from 5.15 to some other number. The default is 5.15*sigma, because 5.15 is the number of standard deviations needed to capture 99% of your process measurements. The last entry in the 5.15*Sigma column is 5.15*Total. This number, usually referred to as the study variation, estimates the width of the interval you need to capture 99% of your process measurements.
–%Contribution—the percent contribution to the overall variation made by each variance component. (Each variance component divided by the total variation, then multiplied by 100.) The percentages in this column add to 100.
–%Study Var—the percent of the study variation for each component (the standard deviation for each component divided by the total standard deviation). These percentages do not add to 100.
–Number of Distinct Categories—the number of distinct categories within the process data that the measurement system can discern. For instance, imagine you measured 10 different parts, and Minitab reported that your measurement system could discern 4 distinct categories. This means that some of those 10 parts are not different enough to be discerned as being different by your measurement system. If you want to distinguish a higher number of distinct categories, you need a more precise gage.
The number is calculated by dividing the standard deviation for Parts by the standard deviation for Gage, then multiplying by 1.41 and rounding down to the nearest integer. This number represents the number of non-overlapping confidence intervals that will span the range of product variation.
The Automobile Industry Action Group (AIAG) [1] suggests that when the number of categories is less than 2, the measurement system is of no value for controlling the process, since one part cannot be distinguished from another. When the number of categories is 2, the data can be divided into two groups, say high and low. When the number of categories is 3, the data can be divided into 3 groups, say low, middle and high. A value of 4 or more denotes an acceptable measurement system.
The Gage R&R study produces six graphs (when operators are entered, otherwise there are only four graphs):
–Xbar Chart by Operator displays the measurements in relation to the overall mean for each operator, allowing you to compare operators to each other, and to the mean.
–R Chart by Operator displays the variation in the measurements made by each operator, allowing you to compare operators to each other.
–Components of Variation is a visualization of the final table in the Session window output, displaying bars for: Total Gage R&R, Repeatability, Reproducibility (but not Operator and Operator by Part), and Part-to-Part variation.
–Operator by Part Interaction displays the Operator by Part effect, so you can see how the relationship between Operator and Part changes depending on the operator.
–By Operator displays the main effect for Operator, so you can compare mean measurement for each operator.
–By Part displays the main effect for Part, so you can compare the mean measurement for each part.
From: ----.----@**************.com
To: ,
Subject: FW: Results from SureBolt Gage R&R
Date: Tue, 21 May 200213:52:00 -0500
Stu,
I apologize for the extreme delay in this e-mail but we are getting very close to our launch date for our ------and things are getting very hectic around here. So, without any further delay, let me try and take care of two things with a single message. First, I did complete the Gage R&R on your SureBolt Ultrasonic measurement system and it performed very well. Attached are the results as calculated in Minitab along with an explanation of what the various items mean. In short, there are a few features that determine if an R&R was successful or not. I.e. The number of distinct categories, % contribution, Xbar Chart & By Bolt No. Chart. Feel free to contact me if you have any questions. Now, the unfortunate part of this e-mail. I really wanted to purchase one of you systems if for no other reason than for ease of use and the ability to compare it to itself to see if the results are correct. However, the plant is very leery about purchasing new technology that doesn't have a "large" distribution or "proven" track record yet. Please don't take offence at what I am saying, I was truly impressed and I believe others were as well in that you have a superior gage. I think one of the biggest problems was that in your presentation you were saying was that the way we had been checking clampload up until now may be incorrect and flawed and that unfortunately may not have set well with some people. Plus the whole fear of change thing.
<Gage R&R Results for SureBolt.doc>
Now onto a better/different topic. Have you ever been asked to develop an algorithm that could accurately check clampload in a yielded bolt. On our new ----- we have two bolts that the product spec will require us to yield the bolt to achieve the required clampload. The bold is being designed as a yield bolt and we are currently trying to develop a correlation between the permanent elongation and the resultant clampload as measured with a Raymond bolt gage. I am hoping that this is something you have had to deal with in your work w/ NASA and if it is currently a function or within the capability of your SureBolt gage, we may still be able to work something out. Until now, nobody here at the plant or in Product Engr. has had a need to intentionally take a bolt to yield. Any advise or help you may be able to offer would be appreciated.
Thank you,
------
------Corporation
Senior Manufacturing Engineer
------
Ph. #: (***) ***-****
Pg. #: (***) ***-****
Fax #: (***) ***-****
E-mail: ……
American Remote Vision Company
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