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Tagged: DPMO sigma level

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

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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.

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.

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”.

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:

Example:

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@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?

@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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