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Variable Gage RR in Minitab

Who is Arved J. Harding, Jr.?. ChristianUnited Methodist. Family ManWife 2 boys. Employee of Eastman Chemical Company for 20 Years (5/10/08). M.S. in Statistics, Va. Tech, 1988. Active volunteer and leader in the Northeast TN Section of the American Society for Quality (ASQ). Hillbilly. Graduate of UVA College at Wise - B.S. in Math, 1985.

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Variable Gage RR in Minitab

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    1. Presented by Arved Harding Prepared by Arved and Wayne Ketron ASQ Tutorials Jan 15, 2009 Variable Gage R&R in Minitab 1

    2. Who is Arved J. Harding, Jr.?

    3. What are we going to cover? What is the purpose of a Variable Gage R&R? Repeatability vs. Reproducibility Generating a Variable Gage R&R study in Minitab How to define part or process tolerance Part selection for the study Analysis of Gage R&R in Minitab Interpreting the variable GRR graphical and statistical tools 3

    4. What Can We Get Out of a Variable Gage R&R? Measure of the % of variation in our process that is caused by our measurement system Compare measurements within and between operators Compare measurements within and between two (or more) measurement devices Provide criteria to accept new measurement systems (consider new equipment) Evaluate a suspect gage Evaluate a gage before and after corrective action (training, repair, replacement, etc) Determine true process variation Ensure that the measurement system is measuring what we want before process improvement Avoid shipping defects to our customers Avoid scrapping perfectly good parts 4

    5. Variable Gage R&R in a Nut-shell We want to characterize variation from the process We usually estimate this with part-to-part variation Can use an estimate from historical data We want to estimate the test variation Repeatability and reproducibility We want to know if the test variation is “good enough” for the application Ratio of Process Variation to Test Variation (% Study Variation) Ratio of Spec Range to Test Variation (P/T Ratio or %Tolerance) 5

    6. Typical Recommended Gage R&R Study Select a product this study will represent Collect 10 parts that represent the expected variation you would see in your process. This could include out of spec parts if this is expected. Mistakes include: Collecting parts that are too close together and do not represent the total variation thus making the test variation look worse than it is. Collecting parts across different products thus making the test variation look much better than it is. 6

    7. Typical Recommended Gage R&R Study Select 3 analysts and have them measure the 10 parts 2 times at random. 60 total measurements Are these numbers magical? Can I use more analysts, parts or repeats? 7

    8. R&R According to Wikipedia R&R (magazine), a music trade magazine R&R (Military), acronym for Rest and Recuperation or Rest and Recreation R&R (EastEnders), a fictional nightclub in EastEnders Rock & Republic, an American designer jeans company Repeatability and reproducibility Rescue and resuscitation "Read and review", a term used in fanfiction by authors looking for feedback "Recent and relevant", a requirement for those training teachers in the UK that they had experience teaching in a school that was both recent and relevant.; 8

    9. What Mork Says When He Laughs? Humor. Ar! Ar! 9

    10. R&R Repeatability – variation due to the measuring device, or the variation observed when the same operator measures the same part repeatedly with the same device. Reproducibility– variation due to the measuring system, or the variation observed when different operators measure the same part using the same device. 10

    11. Gage R&R Crossed Helps assess how well the measuring system can distinguish between parts Whether the operators can measure consistently within and between themselves Assesses test variation Crossed – every part is measured by every person Balanced – the measurement is done the same number of times by each person on each part. 11

    12. Nozzle Example 12

    13. Nozzle Example Specification limits – 9012+- 4 Tolerance or Specification Range= ? By entering a value for Process tolerance in Minitab you get an estimate of the proportion of the tolerance taken up by the test variation. 13

    14. Nozzle example 14

    15. Key Graphs 15

    16. Key Graphs 16

    17. Graph of Variance Components 17

    18. A Few Statistics 18

    19. A Few More Statistics 19

    20. Measures % Contribution – Each value in the VarComp column is divided by the Total variation then multiplied by 100. This column adds to 100%. Study Var (6*SD) – represents the total width of the distribution of the data based on variation from that Source % Study Var (%SV) – Study var for each source divided by Total Study var * 100. Does not add to 100%. %Tolerance (SV/Tolerance) – Percent of spec range taken up by the total width of the distribution of the data based on variation from that Source %Process – is displayed when a historical std dev is entered in Options. 20

    21. Which Measure to Use? If the measurement system is used for process improvement such as reducing part-to-part variation, then %Study variation may be a better measure. If the measurement system is used to evaluate parts relative to specifications, then %Tolerance variation may be a better measure. 21

    22. AIAG Guidelines %Tolerance and % Study Variation 10% or less – Acceptable 10% to 30% - Marginal 30% or greater – Unacceptable %Contribution 1% or less – Acceptable 1% to 9% - Marginal 9% or greater - Unacceptable 22

    23. Number of Distinct Categories The number of distinct categories that can be reliably observed spart / smeasuring system * sqrt(2) Minitab truncates this value except when it is less than 1, in that case Minitab sets the number of distinct categories to 1. 23

    24. One More Chart – The Gage Run Chart 24

    25. Another Example 25

    26. Gage Run Chart 26

    27. Graphs 27

    28. Operator * Pipe Interaction 28

    29. Review the Statistics 29

    30. Creating a Data Collection Worksheet 30

    31. First 30 runs of the 60 run Design 31

    32. Nested Studies Use this for Destructive tests with small batch sizes. Example – Slabs of Stainless Steel 9 slabs are randomly chosen from production. We’re assuming of course the 9 slabs represent the normal variation seen. This may not be true with only 9 selected at random. Randomly assign 3 slabs to each of 3 operators Each impact test is destructive but we can get 3 samples from each slab. We expect very little within slab variation, so testing 3 samples within a slab should be a good estimate of test variation. 32

    33. Key Graphs 33

    34. Gage Run Chart 34

    35. Statistics on Slab 35

    36. Warning Do not apply a variable gage R&R if your measurements use an attribute scale such as pass/fail, or a 1-5 rating. Consider an Attribute Agreement Study for this. That’s another seminar. 36

    37. Questions???? 37

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