# What's a Good DHU Rate? Garment Factory Benchmarks 2026 > DHU benchmarks for garment factories in 2026. What counts as Excellent, Good, Acceptable, Poor, Critical — with real numbers from CMT factories in Bangladesh, India, Vietnam, and Nepal. **Source:** [https://scanerp.pro/blog/dhu-benchmarks-garment-factory-2026.html](https://scanerp.pro/blog/dhu-benchmarks-garment-factory-2026.html) --- What's a Good DHU Rate? Garment Factory Benchmarks 2026 | Scan ERP # What's a Good DHU Rate? Garment Factory Benchmarks 2026 S Santosh Rijal · May 12, 2026 · 10 min read Quality Control ![DHU formula — Defects Per Hundred Units = (Defects Found / Garments Inspected) × 100 with three worked examples](/assets/seo-images/dhu-formula-defects-per-hundred-units-garment.jpg) The DHU formula with three worked examples — 5% Excellent, 14% Acceptable, 30% Critical. Cross-verified against the OnlineClothingStudy industry reference. "What's your factory's DHU?" is the second question every buyer asks after "what's your monthly capacity?" The expected answer is a single number. If you say 12, they go quiet and start asking different questions. If you say 4, they ask when you can ship a sample order. This guide answers the question buyers do not ask but should: **what is a reasonable DHU for a CMT factory in 2026, by garment type, by country, by line maturity?** ## The DHU formula — quick refresher **DHU = (Total defects found / Total garments inspected) × 100.** Critical distinction that trips up new QC supervisors: DHU counts *defects*, not defective pieces. A T-shirt with a broken stitch, a wrong size label, and a fabric hole is *three* defects in one garment. All three count. Example: a checker inspects 250 garments, finds 20 defective pieces with 35 total defects. DHU = 35/250 × 100 = **14**. Not 20/250 = 8. Twenty out of 250 is the rejection rate — a separate metric. ## The universal benchmark scale DHU rangeClassificationWhat it means ≤ 5%**EXCELLENT**World-class. Most lots ship straight to brand without rework. You earn buyer preference and repeat orders. ≤ 10%**GOOD**Industry standard for established CMT factories with mature QC. Buyer inspections pass routinely. ≤ 15%**ACCEPTABLE**Common for newer factories, fashion knits, complex garments. Buyer inspections pass but margin is thin after rework. ≤ 25%**POOR**Rework eats your margin. Buyers complain. You are at risk of failed inspections. > 25%**CRITICAL**Lot rejection becomes routine. Margin is negative after sorting and discount penalties. These thresholds are what we use in our [garment-dhu-calculator](https://www.npmjs.com/package/garment-dhu-calculator) npm package and what most published industry references converge on. Some sources use slightly different bands (e.g. ≤7% Excellent, ≤12% Good) but the structure is the same. ## DHU by garment category "Good DHU" depends heavily on what you are making. A 10% DHU on a complex tailored jacket is excellent. A 10% DHU on a basic T-shirt is unacceptable. Approximate 2026 benchmarks from CMT factories we cross-checked with: Garment typeExcellentGoodAcceptable Basic T-shirt (cotton, no print)≤ 3%≤ 6%≤ 10% Printed T-shirt / polo≤ 5%≤ 8%≤ 12% Hoodie / sweatshirt≤ 6%≤ 10%≤ 14% Formal shirt (woven, button-front)≤ 5%≤ 9%≤ 13% Trouser (5-pocket denim)≤ 8%≤ 13%≤ 18% Tailored jacket / blazer≤ 10%≤ 16%≤ 22% Outerwear (3-layer technical)≤ 12%≤ 20%≤ 28% Lingerie / swimwear≤ 6%≤ 10%≤ 15% Activewear (performance knit)≤ 5%≤ 9%≤ 14% Children's wear≤ 4%≤ 7%≤ 11% The pattern: more operations = higher DHU. A jacket has 60+ operations vs a T-shirt's 8-12 operations. If each operation has a 0.5% defect rate, the cumulative DHU is much higher on the jacket. This is math, not a quality problem — but it means you cannot directly compare DHU between garment types. ## DHU by country / region Country averages are very rough because factory-to-factory variation within any country is enormous. A top Bangladesh factory beats a poor Sri Lanka factory easily. But for orientation: Country / regionTypical DHU range (basic knit)Notes Vietnam4–8%Strong process discipline, mature workforce Bangladesh (RMG, top tier)5–9%Compliance-driven, well-trained at top factories Bangladesh (mid-tier)10–15%Most volume; variable QC investment India (Tirupur knit)6–10%Strong knit cluster, lower for tees, higher for fashion India (Delhi/Noida woven)10–18%Complex garments, more variation Cambodia8–14%Skilled but workforce turnover affects consistency Nepal10–15%Younger industry, growing Sri Lanka4–8%Premium positioning, strong process Ethiopia15–25%New workforce, training-curve heavy China (mid-grade)3–7%Strong process culture, declining workforce These are not official numbers — they are based on our cross-checks with buyer QA teams and other factory owners over the last two years. Treat as orientation, not gospel. ## DHU by line maturity The single biggest variable inside one factory is line maturity. A line that has been running the same style for three months produces dramatically lower DHU than a line that just started a new style yesterday. Line stageDHU multiplier vs steady state Day 1 of new style3–5× higher than steady state Week 1 of new style2–3× higher Week 2-3 of new style1.5× higher Week 4+ (steady state)Baseline This is why **changeover frequency matters more than absolute DHU**. A factory with 10 styles per month and 12% average DHU is probably running better operations than a factory with 2 styles per month at 8% DHU — because the first factory's steady-state DHU after the learning curve is likely 4-5%, while the second's is 6-7%. If you are a buyer evaluating a factory, ask for DHU broken out by week-of-style. If a factory does not track this, that itself tells you something about their QC maturity. ## What drives DHU — in order of impact From our own data (see the [full DHU reduction case study](/blog/reduce-rejection-rate-dhu-garment-factory.html)): ### 1. Machine condition (single biggest factor) Of our 35 machines, 14 had issues we did not see until we audited: bad timing, dull needles, oil leaks. After fixing all 14, our skip-stitch rate dropped 60% and puckering dropped 45%. **Machine maintenance is the highest-ROI DHU intervention.** ### 2. Operator skill matrix Putting an overlock-skilled operator on a single-needle machine produces 3-4× the DHU of someone trained on that machine. Skill matrix discipline is invisible until you measure it. ### 3. Pre-production sample issues that did not get fixed If the sample had a measurement issue and you "fixed it in production", that issue is going to show up at scale. Every PP sample defect is a future DHU contribution. ### 4. Fabric inspection gate Fabric defects (slubs, weaving issues, shading) account for 15-25% of our DHU. Investing in a 4-point fabric inspection system (separate post — [guide here](/blog/fabric-inspection-4-point-system-guide.html)) catches these before they hit the line. ### 5. Inspector calibration Two inspectors looking at the same 100 garments will find different DHUs unless you calibrate them. We run a monthly calibration where 5 inspectors check the same lot — the spread reveals whose count to trust. ## Free online DHU calculator The DHU calculator on our [tools page](https://scanerp.pro/tools/#dhu-calc) runs in your browser — enter defects + garments inspected, get DHU + classification + benchmark badge instantly. For factory ERP integration, we open-sourced the math: - **npm:** `npm install garment-dhu-calculator` - **PyPI:** `pip install garment-dhu-calculator` Both packages support breakdown by defect type, multi-checker daily aggregation, and benchmark classification. MIT licensed, 27 inline tests cross-verified against OnlineClothingStudy's worked example. OPEN SOURCE · MIT ### Track DHU in your own QC app DHU formula + breakdown by defect type + multi-checker daily aggregation + benchmark classification. MIT licensed. $ npm install garment-dhu-calculator $ pip install garment-dhu-calculator [Try it live →](/tools/#dhu-calc) [See all 8 packages →](/blog/open-source-garment-toolkit.html) ## Related reading - [From 8.2% rejection to under 3%: our DHU reduction playbook](reduce-rejection-rate-dhu-garment-factory.html) - [AQL sampling for garment inspection (ISO 2859-1)](aql-sampling-garment-inspection-iso-2859.html) - [4-point fabric inspection system guide](fabric-inspection-4-point-system-guide.html) - [Open-source garment industry toolkit — 8 free calculators](open-source-garment-toolkit.html) --- Built by [Scan ERP](https://scanerp.pro/) — QR-based ERP for CMT garment factories.