Calculator Inputs
Example Data Table
| Batch | Total Units | Inspected | Defective Units | Total Defects | Reworked |
|---|---|---|---|---|---|
| Shift A | 10,000 | 8,000 | 180 | 245 | 110 |
| Shift B | 9,500 | 7,800 | 126 | 168 | 94 |
| Shift C | 11,200 | 8,400 | 214 | 301 | 150 |
Formula Used
Defective Rate = Defective Units ÷ Inspected Units
Yield Rate = (Inspected Units − Defective Units) ÷ Inspected Units
DPU = Total Defects ÷ Inspected Units
DPO = Total Defects ÷ (Inspected Units × Opportunities per Unit)
DPMO = DPO × 1,000,000
Scrap Rate = (Defective Units − Reworked Units) ÷ Inspected Units
Estimated Cost of Poor Quality = Scrap Units × Cost per Scrapped Unit
Rolled Throughput Yield = e−DPU
Estimated Sigma Level ≈ NORMSINV(1 − DPMO ÷ 1,000,000) + 1.5
Confidence Interval uses the Wilson score method for a binomial defective proportion.
How to Use This Calculator
Enter total production volume and the inspected sample size first. Add defective units, total defects, and opportunities per unit to capture both unit failures and defect frequency.
Include reworked units to separate salvageable output from true scrap. Enter a scrap cost to estimate direct loss from poor quality.
Set a target defective rate and preferred confidence level, then submit the form. Review the result cards, detailed table, and export buttons for reporting.
Use the defective rate for unit-level quality tracking, DPMO for Six Sigma style benchmarking, and the confidence interval to judge sampling uncertainty.
FAQs
1. What does defective rate measure?
Defective rate shows the share of inspected units that failed quality requirements. It focuses on bad units, not the total number of individual defects inside each unit.
2. Why track both defective units and total defects?
Defective units show how many products failed. Total defects show how many issues were found overall. A single unit can contain multiple defects, so both measures reveal different process problems.
3. What is the difference between DPMO and PPM?
PPM is based on defective units only. DPMO adjusts for multiple defect opportunities in each unit, making it more useful when products have many inspection points.
4. Why is inspection coverage important?
Coverage shows how much of total production was actually inspected. Low coverage can make reported defect rates less representative, especially when defect patterns vary by shift or machine.
5. What does the confidence interval tell me?
It gives a likely range for the true defective rate based on your inspected sample. Wider intervals mean more uncertainty, often caused by smaller sample sizes.
6. Why include reworked units?
Reworked units separate recoverable failures from actual scrap. That helps estimate both process waste and the financial impact of defects more accurately.
7. Can I use this for batch comparisons?
Yes. Run each batch with the same opportunity assumptions and inspection rules. Then compare defective rate, DPMO, sigma level, and scrap cost across periods.
8. What actions should follow a high defective rate?
Check where defects cluster by product, shift, machine, operator, or supplier. Then validate measurement systems, review control limits, and target the biggest root causes first.