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1. Lean Six Sigma – Green Belt Workshop
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Part 9

2. 2
A desired resolution of 0.5% means that the gage needs to distinguish a difference of half
percentage point. If the sample size is hundred, the gage is good to distinguish a difference of one
percentage point only (1/100), which may not solve the purpose.
Attribute gage sheet:
Attribute Gage Examples
Measure

3. 3
EV and AV
Total variation (R&R) in a measurement system is further classified as:
 Equipment Variation: The variation within operator, within equipment or gage, within the
method. This variation comes from the parts of measurement system or process. This is also
termed as Repeatability variation.
 Appraiser Variation: The variation introduced between different operators, different parts, and
different methods. This is also termed as Reproducibility variation.
Total variation (R&R) = EV + AV
The mathematical equation used for representing the relationship between total variation, EV and
AV is
(Std. Dev (R&R))2 = (Std. Dev (Repeatability))2 + (Std. Dev. (Reproducibility))2
Measure

4. 4
How a gage plays with Spec Limits
What is the challenge with having high R&R error ?
Following scenario explains why..
Measure

5. 5
Gage ANOVA - Objectives
Gage ANOVA study:
 Quantify amount of measurement variability
 Identify amount of measurement variation from different sources
Data Type: Continuous
The data should be arranged in columns as in the
following example. The
recommended numbers of operators, parts and trials are
3, 10 and 3 respectively.
Which would give one 90 data points. (3*10*3=90)
Measure

6. 6
Gage ANOVA Minitab
Measure

7. 7
Gage ANOVA –Minitab
Measure

8. 8
Minitab Session Output
Measure

9. 9
Percentage contribution:
It represents the percentage of variation contributed by gage in the process.
Recommended percentage contribution from Total Gage R&R should ideally be less than 10%.
However one should consult with BB/MBB if the value is between 10-15%, where one might accept
the gage error and gets go ahead with the project. Project should be evaluated by the mentor and
acceptance would depend on the process, business and the project champion.
If tolerance is beyond 15% it is recommended that the gage be corrected before repeating the gage
study.
No. of Distinct Categories:
This number represents the number of distinct groups in the data. For example if you have 20 part
being evaluated and the number of distinct categories are 2. This means that the most of the parts
are not different enough, and the data can be divided into two groups. In such a case the precision
of the gage is not enough for the process. Minimum number of distinct categories should be at least
5.
Measure

10. 10
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