iSixSigma

GRR – prove significant improvement

Six Sigma – iSixSigma Forums Old Forums General GRR – prove significant improvement

Viewing 7 posts - 1 through 7 (of 7 total)
  • Author
    Posts
  • #51691

    Stefan Szemkus
    Participant

    Hi everybody,
    I read this forum for several moths but this is the first post I do – I hope i do everything correct.
     
    My question:
    How can I determine to have achieved a significant improvement of my measurement system when I execute a GRR before and after a change of the measurement system.
    E.g.: I did an initial GRR and got 82% (versus Total Variation), then I changed the measurement process and repeated the GRR, using the same parts and appraisers => I achieved 33% GRR.
    Although it obviously looks like a significant improvement, I would like to prove that.
    Could you help me? How do you prove improvements of GRR results?
     
    Many thanks in advance,
    Stefan

    0
    #179813

    Remi
    Participant

    Hai Stefan.
    Strange question. Generally you want to prove that your measurement system is Ok to ensure that data analysis on the measured data can be trusted (i.e. the data analysis gives outcomes that can be connected to the situation the data describes). So as soon as you are good enough  (<10% or 30% whatever your treshold is) then that's it.
    But here is what I thought up (if it is wrong another expert will probably correct, but you may have to wait for Monday since some of them are at the i6S-summit):
    You can prove that you changed significantly with the Equal Variances test. But you have to do that not on all the variance but on the measurement variance only. Take the two datasets of the gage r&R investigations. For each dataset seperately do the following:

    Substract from each datapoint the average measured value of the product.
    This way you have neutralised the product variation in your data. All the variation left in the dataset is the variation ’caused’ by repeats and operator change.
    Now perform an Equal Variances test on the two datasets. It will hopefully show that there is a significant change.
    Good Luck.
    Hmm, at rereading i found a possible flaw. With my ‘solution’ you will compare the absolute variances while the gage r&R investigates relative variances. I’ll have to think some more about this.
     

    0
    #179814

    Eoin
    Participant

    Hi StefanIf you remeasure your components and recalculate
    your process capability index (Pp or Ppk) you will/
    should see and improvement in it – it will increase
    – as the contribution to the overall variation
    observed made by the measurement system variation
    decreases. This will also result in a narrower
    tolerance interval. Practically you will see less “good” parts being
    rejected in error due to measurement system error
    or less escapes. Have you a control chart in place?
    You might consider recalculating the control limits
    on the charts after a little while. By the sound of things you have made a significant step forward but you still have more to do to
    improve the gauge. Best of luck
    Eoin

    0
    #179838

    Bower Chiel
    Participant

    Hi Stefan
    William Woodall and Connie Borror published a paper entitled “Some Relationships between Gage R&R Criteria”. It is available at http://www3.interscience.wiley.com/cgi-bin/fulltext/114280277/PDFSTART. They refer to another paper by Burdick, Borror and Montgomery entitled “Design and Analysis of Gage R&R Studies” which gives formulae for calculating confidence intervals for % Gage R&R. If you calculated 95% confidence intervals before and after and got say 70% to 94% before and 20% to 66% after the fact that these intervals don’t overlap would provide reassurance of a real improvement. Statistical purists would likely object but it might be worth looking at.Best WishesBower Chiel

    0
    #179944

    Stefan Szemkus
    Participant

    Dear remi,
    thank you very much for the quick reply on my question. I was really astonished that you bothered with my problem in that short time.
    Would you say it is not necessary to prove the significance on the improvement? I always have been teached to prove those things, but perhaps that is not the way it works in practice.
    If I want to execute a 2-variances-test, what are the degrees of freedom I have to choose? Could you help me also with this question?
    Thank you very much in advance,
    Stefan

    0
    #179945

    Stefan Szemkus
    Participant

    Dear Eoin,
    thank you very much for answering my question.
    I’m very angry with myself, because the way you proposed to prove significance should have come into my mind too.
    Again, thank you very much!
    Best regards,
    Stefan

    0
    #179947

    Stefan Szemkus
    Participant

    Dear Bower Chiel,
    thank you very much for the detailled reply. I will get the papers and do the CI calculations.
    If I do all three recommended calculations (2-variances-test, Cpk-calculation and CI-calculation) that should give evidence enough to prove significance, shouldn’t it.
    Best regards,
    Stefan

    0
Viewing 7 posts - 1 through 7 (of 7 total)

The forum ‘General’ is closed to new topics and replies.