In: Statistics and Probability
((Note: The answer has to be typed, not hand written nor a picture.)) Thank you.
GAGE R & R EXERCISE
in this example, we do a gage R&R study on two data sets: one in which measurement system variation contributes little to the overall observed variation (GAGEAIAG.MTW), and one in which measurement system variation contributes a lot to the overall observed variation (GAGE2.MTW). For comparison, we analyze the data using both the ANOVA and the Xbar and R method.
The GAGEAIAG data was taken from Measurement Systems Analysis Reference Manual, 3rd edition. (Chrysler, Ford, General Motors Supplier Quality Requirements Task Force). Ten parts were selected that represent the expected range of the process variation. Three operators measured the ten parts, three times per part, in a random order.
For the GAGE2 data, three parts were selected that represent the expected range of the process variation. Three operators measured the three parts, three times per part, in a random order
Part 1: Use the ANOVA method with GAGEAIAG data
1 Open the worksheet GAGEAIAG.MTW.
2 Choose Stat > Quality Tools > Gage Study > Gage R&R Study (Crossed).
3 In Part numbers, enter Part.
4 In Operators, enter Operator.
5 In Measurement data, enter Measurement.
6 Under Method of Analysis, choose ANOVA.
7 Click Options. Under Process tolerance, choose Upper spec - Lower spec and enter 8.
8 Click OK in each dialog box.
Answer the following questions
1. In the session window output, what is the percent contribution for part-to-part? _____
2. In the session window output, what is the percent contribution for total Gage R & R? _____
3. After answer questions 1 and 2 above, which do you, believe causes more of the variation, part-to- part or the measuring system? ________________________________
4. If you knew that according to Automobile Industry Action Group (AIAG) that you can determine whether or not your measurement system is acceptable using the following guidelines.
If the Total Gage R&R percentage in the %Study Var column (% Tolerance, %Process) is: PAGE 1
Gage R & R EXERCISE
Less than 10% - the measurement system is acceptable
Between 10% and 30% - the measurement system is acceptable depending on the application, the cost of the measuring device, cost of repair, or other factors
Greater than 30% - the measurement system is unacceptable and should be improved
If you are looking at the % Contribution column, the corresponding standards are:
Less than 1% - the measurement system is acceptable
Between 1% and 9% - the measurement system is acceptable depending on the application, the cost of the measuring device, cost of repair, or other factors.
What have you determined about this measurement system based on the %Study Var column for total Gage R &R?___________________________________________________
_________________________________________________________________
5. Looking at the graph window output, what does the components of variation graph in the top upper left hand corner indicate?__________________________________________________
__________________________________________________________________________
6. Looking at the measurement by operator graph, which operator seems to measure differently than the others? ________________
Step 2: Use the ANOVA method with GAGE2 data
1 Open the file GAGE2.MTW.
2 Choose Stat > Quality Tools > Gage Study > Gage R&R Study (Crossed).
3 In Part numbers, enter Part.
4 In Operators, enter Operator.
5 In Measurement data, enter Response.
6 Under Method of Analysis, choose ANOVA.
7 Click OK. PAGE 2
GAGE R & R EXERCISE
Answer the following questions
1. In the session window output, what is the percent contribution for Total Gage R&R? _____
2. In the session window output, what is the percent contribution for total part-to-part? _____
3. After answer questions 1 and 2 above, which do you, believe causes more of the variation, part-to- part or the measuring system? ________________________________
4. If you knew that according to Automobile Industry Action Group (AIAG) that you can determine whether or not your measurement system is acceptable using the (criteria from part 1)
What have you determined about this measurement system based on the %Study Var column for total Gage R &R?___________________________________________________
5. Looking at the graph window output, what does the components of variation graph in the top upper left hand corner indicate?__________________________________________________
__________________________________________________________________________
6. Looking at the repsonse by operator graph, which operator seems to measure differently than the others? ________________
Answer:
By using given data,
Part-1
Results for: Gageaiag.MTW as follows bellow
Gage R&R Study - Here, ANOVA Method is followed
Two-Way ANOVA Table With Interaction
Source DF SS MS F P
Part 9 88.3619 9.81799 492.291 0.000
Operator 2 3.1673 1.58363 79.406 0.000
Part * Operator 18 0.3590 0.01994 0.434 0.974
Repeatability 60 2.7589 0.04598
Total 89 94.6471
α to remove interaction term is = 0.05
Two-Way ANOVA Table Without Interaction
Source DF SS MS F P
Part 9 88.3619 9.81799 245.614 0.000
Operator 2 3.1673 1.58363 39.617 0.000
Repeatability 78 3.1179 0.03997
Total 89 94.6471
Gage R&R
%Contribution
Source VarComp (of VarComp)
Total Gage R&R 0.09143 7.76
Repeatability 0.03997 3.39
Reproducibility 0.05146 4.37
Operator 0.05146 4.37
Part-To-Part 1.08645 92.24
Total Variation 1.17788 100.00
Process tolerance = 8
Study Var %Study Var %Tolerance
Source StdDev (SD) (6 × SD) (%SV) (SV/Toler)
Total Gage R&R 0.30237 1.81423 27.86 22.68
Repeatability 0.19993 1.19960 18.42 14.99
Reproducibility 0.22684 1.36103 20.90 17.01
Operator 0.22684 1.36103 20.90 17.01
Part-To-Part 1.04233 6.25396 96.04 78.17
Total Variation 1.08530 6.51180 100.00 81.40
Number of Distinct Categories are = 4
(1) The percent contribution for part-to-part =92.24%
(2) The percent contribution for total Gage R & R =7.76%
(3) We believe part-to-part causes more of the variation
(4) We observe that Total Gage R&R percentage in the %Study Var column is 27.86%. So, the measurement system is acceptable depending on the application, the cost of the measuring device, cost of repair, or other factors
(5) This shows, that part-to part contribute more towards variations as compared to other factors.
(6) Looking at the measurement by operator graph, operator-C seems to measure differently than the others
Results for: Gage2.MTW is follows bellow
Gage R&R Study - Here ANOVA Method is followed
Two-Way ANOVA Table With Interaction
Source DF SS MS F P
Part 2 38990 19495.2 2.90650 0.166
Operator 2 529 264.3 0.03940 0.962
Part * Operator 4 26830 6707.4 0.90185 0.484
Repeatability 18 133873 7437.4
Total 26 200222
α to remove interaction term = 0.05
Two-Way ANOVA Table Without Interaction
Source DF SS MS F P
Part 2 38990 19495.2 2.66887 0.092
Operator 2 529 264.3 0.03618 0.965
Repeatability 22 160703 7304.7
Total 26 200222
Gage R&R
%Contribution
Source VarComp (of VarComp)
Total Gage R&R 7304.67 84.36
Repeatability 7304.67 84.36
Reproducibility 0.00 0.00
Operator 0.00 0.00
Part-To-Part 1354.50 15.64
Total Variation 8659.17 100.00
Process tolerance = 8
Study Var %Study Var %Tolerance
Source StdDev (SD) (6 × SD) (%SV) (SV/Toler)
Total Gage R&R 85.4673 512.804 91.85 6410.05
Repeatability 85.4673 512.804 91.85 6410.05
Reproducibility 0.0000 0.000 0.00 0.00
Operator 0.0000 0.000 0.00 0.00
Part-To-Part 36.8036 220.821 39.55 2760.27
Total Variation 93.0547 558.328 100.00 6979.10
Number of Distinct Categories = 1
Gage R&R for Response
GAGE R & R EXERCISE
Answers for the questions are
(1) The percent contribution for Total Gage R&R=84.36
(2) The percent contribution for total part-to-part=15.64
(3) We believe measuring system causes more of the variation
(4) We observe that Total Gage R&R percentage in the %Study Var column is 91.85% Greater than 30% -so the measurement system is unacceptable and should be improved.
(5) Looking at the graph window output, the components of variation graph in the top upper left hand corner indicate that the measurement system explained most of the variaiton and within this repeatability explained most variation.
(6) Looking at the repsonse by operator graph, operator-1 seems to measure differently than the others.