Defects Per Million Opportunity (DPMO)

Defects per million opportunity (DPMO) is a measure of occurrence of defects per million opportunity. It is calculated by the formula shown in the picture below.

Here D is the No of defects observed, S is the sample size and O is the no of opportunities for defects per unit. This will be more clear from the following example.

Example

A company produces a product A. The quality personal of the company wants to know the DPMO of an operation, which is moulding of a small plastic part. So he decided a shift and day to collect sample. He collected 100 samples from a duration of 3 hours. He stayed near the moulding machine throughout the three hours!!!. And he inspected each and every plastic parts for defects. Before he coming to the shop floor, he has collected some data from the previous experience and past data and arrived a conclusion on what all are the possibilities of having a defect in moulding and he found around 12 defect opportunities per unit. Some of them are short mould, flash, dust, discoloration, presence of oil content, etc. And he found around 136 defects after inspecting 100 samples.

Calculation

No of defects observed, D = 136

Sample size, S = 100

No of opportunities for defect per unit, O = 12

Defects per million opportunity, DPMO = (136 /(12 x 100)) x 1000000

= 113333.33

Don’t waste your time in using calculator and pen in calculating DPMO, I have created an online DPMO calculator for calculating DPMO easily and its link is below.

So upto now we know what is DPMO, what is the formula for calculating DPMO, how is it calculated. Ok now some words on why we are calculating DPMO. By calculating DPMO we can know the present quality level of our operation and analyze how well our operations are performing. After knowing DPMO, we can know where we are and where we want to be. This knowledge and thinking will trigger on how we can improve the operations. That’s all for DPMO.

Thank You for reading.

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Lungile Luthuli
Lungile Luthuli
4 years ago

Hi

So refreshing! Clear and concise.

Thanks
L. Luthuli