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Topic From DPMO to Sigma Level

From DPMO to Sigma Level

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This topic contains 5 replies, has 4 voices, and was last updated by  Strayer 5 days, 17 hours ago.

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  • #702847 Reply

    I have a question regarding DPMO. If you calculate DPMO, why would you want to look up the corresponding sigma level? And does it have any meeting as the DPMO can consist of multiple items with (often) non-normal distribution of some of these items.

    #702876 Reply

    It’s easier to compare small numbers. More importantly, the sigma level is statistically more meaningful – Look at a bell curve. The differences get finer as you approach the tails and sigma level accounts for that while DPMO doesn’t. For instance the difference between 2 and 3 sigma is 42,851 DPMO. The difference between 3 and 4 is just 2,636. For your second question, if you aren’t looking at a single specification it’s mixing apples and oranges. But it doesn’t really matter as long as you’re accurately counting defects and opportunities and you’re clear about what’s included. The distribution is irrelevant.

    #702903 Reply

    If the opportunities are truly the value added ones, then DPMO is a fantastic tool to measure across services, product lines, etc. And since sigma level is well known, it’s great.

    ONLY problem is the question has to be asked–did they shift the number or do straight read from Z table. And….some tables are shifted already “being helpful”.

    #702969 Reply

    The Sigma level with DPMO is a approximation to normal distribution from binomial distribution; according with central limit theory, its due to the DPMO measure the number of trials and success (%) in each sample or success (%) in the Critical characteristic of the part. Remember that a part could have many opportunities to evaluate (CTQ’s).

    Example : Suppose that we have a process with this characteristic:
    Units/shift = 30,000
    Defective parts = 300
    Defects observed = 350
    Opportunities = 15
    Dpu = 350/30,000 = .011
    DPMO = (.011/15) x 1,000,000 = 777
    Yield : 1-(0.011/15) = 99.9922%
    ZBench : 3.164 *From normal distribution tables
    Sigma Level: 4.664
    CPk Process: 1.55

    #703277 Reply

    @Straydog Thanks. Never thought about that. This implies that it is more and more difficult to achieve higher sigma scores, the higher your current score is. Am i right?

    @gomezmgab Thanks. But this implies that the transformation from binominal to a normal distribution can only be done when p is not that high, isn’t?

    #703315 Reply

    @erik2018 That’s sort of right. Keep in mind that the closer you get to zero defects the smaller the change necessary to raise sigma level. Improving a few DPMO won’t make much difference if your sigma level is low. But it will the closer you get to 6 sigma or even better where those small DPMO improvements get more and more difficult.

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