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How To Calculate Dpmo

DPMO Formula:

\[ DPMO = \frac{Number\ of\ Defects}{(Number\ of\ Units \times Number\ of\ Defect\ Opportunities\ per\ Unit)} \times 1,000,000 \]

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1. What is DPMO?

DPMO (Defects Per Million Opportunities) is a measure of process quality that represents the number of defects in a process per one million opportunities. It's commonly used in Six Sigma methodologies to quantify process performance.

2. How Does the Calculator Work?

The calculator uses the DPMO formula:

\[ DPMO = \frac{Number\ of\ Defects}{(Number\ of\ Units \times Number\ of\ Defect\ Opportunities\ per\ Unit)} \times 1,000,000 \]

Where:

Explanation: The formula normalizes defect rates across different process complexities by accounting for the number of opportunities for defects in each unit.

3. Importance of DPMO Calculation

Details: DPMO provides a standardized way to compare quality across different processes, products, or services. It helps identify improvement areas and track quality improvement initiatives.

4. Using the Calculator

Tips: Enter the total number of defects found, the number of units produced or processed, and the number of potential defect opportunities per unit. All values must be positive integers.

5. Frequently Asked Questions (FAQ)

Q1: What's considered a good DPMO score?
A: In Six Sigma, 3.4 DPMO is considered "Six Sigma" quality. Below 233 DPMO is 5σ, below 6,210 is 4σ, and below 66,807 is 3σ.

Q2: How is DPMO different from DPU?
A: DPU (Defects Per Unit) counts total defects divided by total units, while DPMO accounts for the complexity (opportunities) of each unit.

Q3: What counts as a defect opportunity?
A: Any characteristic of a unit that doesn't meet requirements. For example, a form with 10 fields has 10 opportunities per unit.

Q4: Can DPMO be greater than 1,000,000?
A: Yes, if the number of defects exceeds the total opportunities (units × opportunities per unit).

Q5: How does DPMO relate to Sigma levels?
A: DPMO can be converted to Sigma levels using standard normal distribution tables to measure how far the process mean is from the nearest specification limit.

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