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					                                                                                                                                                    Gage name:            Sure Bolt
Gage R&R (ANOVA) for Sure Bolt Ultrasonic                                                                                                           Date of study :
                                                                                                                                                    Reported by :
                                                                                                                                                                          Mar 8, 2002
                                                                                                                                                                          Stu Gleman, Dav id Drake
Measurement Equipment                                                                                                                               Tolerance:

                                                         Xbar Chart                                                                                                   By Bolt No.
                                 1       2       3       4        5       6       7       8       9       10

                         16000                                                                                                              16000
Sample Mean

                         15500                                                                                  3.0SL=15517                 15500

                                     1       2       3       4        5       6       7       8       9    10                                          1    2    3    4      5   6    7     8       9   10
                                                                 Bolt No.                                                                                                 Bolt No.

                                                                 R Chart                                                                                   Components of Variation
                                 1       2       3       4        5       6       7       8       9       10                                                                                                 %Total Var
                          150                                                                                   3.0SL=146.0                  100
                                                                                                                                                                                                             %Study Var
          Sample Range


                                                                                                                                  Percent     50

                            0                                                                                   -3.0SL=0.00E+00
                                     1       2       3       4        5       6       7       8       9    10                                              Gage R&R                  Part-to-Part
                                                                 Bolt No.
Gage R&R

Source:             Var. Comp.   Std. Dev.      5.15*Sigma

Total Gage R&R        1042           32.286          166.27
   Repeatability      1042           32.286          166.27
Part-to-Part        145034          380.834         1961.29
Total Variation     146077          382.200         1968.33

Source:             %Contribution     %Study Var.

Total Gage R&R            0.71           8.45
   Repeatability          0.71           8.45
Part-to-Part             99.29          99.64
Total Variation         100.00         100.00

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
Subject: FW: Results from SureBolt Gage R&R
Date: Tue, 21 May 2002 13:52:00 -0500

      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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