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how to calculate sigma for attribute data of process

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  • #41151

    Ruddy
    Participant

     how to calculate sigma for attribute data of process

    I have a process is coating for the production. Totally, I had 10 products, the defect is coating spoliation, Now the point is some product have 0 defect, someone have 3 defects and so on, I used Mintab calculate it, total defects are 17, opportunity is 1, unit is 10, but I can’t get result,defect  opportunity  uint   1             1            1   3             1            1   1             1            1   1             1            1   0             1            1   2             1            1   1             1            1   5             1            1   0             1            1   3             1            1it show** Error ** Incorrect data – result contains a value of PPM inexcess of 1,000,000 (this is impossible);Execution aborted.I think the problem is “opportunity”? but how can I define the opportunity?, anyway the defect is same kind and have a some standard(only compare with a sample about it’s dimension)Does anybody can give me some suggestion? thanks

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    #128704

    Ropp
    Participant

    If the opportunity is one, the it is impossible for a single unit to have three.  Isn’t opportunity in this case how many ways a single unit can be defective?Dave

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    #128706

    Ken Feldman
    Participant

    If you are assuming an opportunity of 1 then you are dealing with defectives not defects.  It is either good or bad.  If you want to do that then just take the number of bad ones regardless of how many defects it had.  If you want to use defects, then you have to consider how many different types of defects are possible and that becomes your opportunity.

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    #128720

    BTDT
    Participant

    Model it as a Poisson distribution with a mean of 1.7.We did the distribution of paint defects/unit area and did a square root transformation to get a normal distribution (I think).Just an idea.Got to go.BTDT

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    #128735

    Ruddy
    Participant

    thanks for your suggestion.
    Now the point is we want to reduce the defect sas possible as we can( because it is costly for us). I think it should belong to attribute data. So does anybody can give me a clear way to define opportunity or  how to calcualte it. 
    thanks

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    #128819

    BTDT
    Participant

    Michael:Sorry for the delay.As I pointed out before, your data can be modeled using a Poisson distribution where the mean number of defects per unit (DPU). When you have a Poisson distribution, you can calculate the probability of finding an item with zero defects using the equation;p(0 defects) = exp(-DPU)Using your data, I count 17 total defects in the 10 units of your sample. The DPU is 1.7 and I get p(0 defects) = 0.182684 all other units will have AT LEAST one defect and be unacceptable to the customer.The number of items with AT LEAST one defect is 1-0.182684 = 0.817316DPMO = 817316This extends Darth’s point about defects and defectives. When a unit has at least one defect, then it is not acceptable to the customer. Counting the number of defects per unit, however, allows you to see if the process is improving at the process level, even though the customer sees the entire unit.When it comes to screening for Vital Xs, use a Chi-square test to see if there are differences in the numbers of defects per unit broken out by subgroups.Does that help? Let me know.Cheers, BTDT

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    #129041

    Ruddy
    Participant

    Hi BTDT,
    It is so nice to get your kind help, I do appreciate that.
     
    Michael

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