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Apply control limits to a non-normal distribution

Discussion in 'SPC - Statistical Process Control' started by Nuno Sardo, Nov 9, 2018 at 10:48 AM.

  1. Nuno Sardo

    Nuno Sardo New Member

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    Hello

    I have a process parameter that is controlled this way:

    If the equipment signal response is below a certain level, we know for sure that the result will be lower than 10% and thus reported as <10.

    However, if a signal response is a little bit higher, then I have to actually quantify the value. In this cases, I usually get results around 5-6, which are still below the 10.

    My data distbitution is something like this:

    Sample size - 126
    Analysis result | Number of events | Cumulative Count | Cumulative %
    <10 | 97 | 97 | 77%
    5 | 16 | 113 | 90%
    6 | 9 | 122 | 97%
    7 | 3 | 125 | 99%
    8 | 1 | 126 | 100%

    What would be the best distribution to fit this data? Exponential? Weibull? Gamma?

    The purpose is to define an upper control limit, as the ones used for normal distributions in SixSigma (average+3sigma). How should I proceed in this case?

    Thanks in advance for your support
     

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