DHU stands for defects per hundred units. It is the most common quality measure on garment sewing lines. It tells you how many defects are found for every 100 garments checked.
The formula#
A garment can have more than one defect, so DHU can be higher than 100 in extreme cases. That is the key difference from defective percentage.
DHU vs defective percentage#
| Measure | Formula | Counts |
|---|---|---|
| DHU | Defects / units checked × 100 | Every defect |
| Defective % | Defective units / units checked × 100 | Garments with at least one defect |
If 100 garments are checked and 8 garments have defects, with a total of 11 defects between them:
- DHU = 11 / 100 × 100 = 11
- Defective % = 8 / 100 × 100 = 8%
DHU gives a fuller picture of the work needed to fix garments. Defective % tells you how many garments need attention.
Worked example: end-of-line checking#
A checker inspects 450 shirts in a day and records these defects:
| Defect | Count |
|---|---|
| Open seam | 9 |
| Skipped stitch | 7 |
| Uneven stitch | 6 |
| Puckering | 5 |
| Stain | 4 |
| Measurement out of tolerance | 3 |
| Total | 34 |
DHU = 34 / 450 × 100 = 7.6
The top three defects (open seam, skipped stitch, uneven stitch) make up 22 of 34 defects, or 65%. That is where to act first.
Using DHU data#
By operation#
Record which operation caused each defect. Then DHU by operation shows the stations that produce most defects. This links quality directly to operators and machines.
By hour#
Hourly DHU shows when problems start: after a break, after a machine adjustment, or when a new operator joins.
Pareto#
Rank defects by count. A small number of defect types usually cause most of the problem. Work on those first with root cause analysis.
What counts as a defect#
Agree a clear defect list with definitions, preferably with photos, before you start measuring. Different checkers counting different things makes DHU meaningless. Classify defects by severity (critical, major, minor) where the buyer's requirements use those classes.
Targets#
DHU targets vary widely with product, buyer and factory. Set a target from your own data, then lower it as problems are fixed. A target that is copied from another factory or product type tells you very little.
Common mistakes#
- Mixing inline and end-of-line DHU in one number.
- Counting only defective garments and calling it DHU.
- Not recording the operation that caused the defect.
- Checking a different sample size each day without noting it.
- Hiding defects by repairing garments before they reach the checker.
Use the DHU calculator for quick calculations, the DHU report template for daily records, and see right first time for a related measure.
DHU at different check points#
Factories often measure DHU at several points. Keep them separate:
| Check point | What it tells you |
|---|---|
| Inline (roving checks) | Defects made at specific operations, found early |
| End of line | Defects in completed garments before finishing |
| Finishing and packing audit | Defects that escaped the line, plus finishing defects |
| Final inspection | What the buyer's inspector sees |
A low end-of-line DHU with a high final inspection DHU means defects are being missed or created after the line.
Related guides#
- Inline inspection: measuring DHU by operation during production.
- Sewing defects: the defect types to count.
- Final inspection: the inspection DHU is meant to prepare for.
- AQL in garment inspection: how the buyer samples finished lots.
Frequently asked questions#
Is a lower DHU always better? Yes, if the checking is honest and consistent. A sudden fall in DHU with no change in the process can mean checking has become less strict.
Should repaired garments be counted again? Count the defects found at the first check. Garments that return after repair are counted separately, so the DHU reflects the line's first-pass quality.