Technical Article · Plant Operations & Cost Management
The complete framework for tracking where your zinc goes, what it costs, and the five operational levers that control it — without spending a single riyal on new equipment
Zinc is the single largest variable cost in a hot-dip galvanizing plant. It is also the cost that most plant managers understand least precisely. They know their zinc bill at the end of the month. Few know exactly how much went on the product, how much went into dross, how much went into ash, and whether any of those numbers are normal or abnormal for their work mix.
This article presents the complete framework I use across my three plants to measure zinc efficiency: the formulas, the industry benchmarks, what the numbers tell you when they are outside target, and the five operational controls that govern them — all requiring nothing more than an accurate scale, a lab iron test kit, and a shift log.
If you can measure it, you can manage it. If you manage it, you stop leaving money on the bath surface every shift.
A complete HDG plant KPI system covers four operational domains. Each domain has one primary metric that tells most of the story, and supporting metrics that explain it when it is outside target.
| Domain | Primary KPI | Supporting Metrics |
|---|---|---|
| Production Volume | Tonnes galvanized per month | Batches per shift · Average batch weight · Days operated |
| Zinc Efficiency | Zinc consumption % | Pickup % · Dross % · Ash % · Net zinc cost per tonne |
| Quality | First-pass rate (%) | Rework batches · Thickness compliance rate · Customer complaints |
| Equipment Effectiveness | Capacity utilisation (%) | Kettle uptime · Unplanned downtime hours · OEE |
These twelve metrics, tracked monthly, give a complete picture of operational health. None of them require sophisticated data systems. Most can be calculated from a batch weight log, a zinc stock record, and a quality inspection register — tools every plant should already have.
Before measuring efficiency, you must understand the model. Every kilogram of zinc that enters the bath must be accounted for. There are only three destinations: on the product, into dross (kettle bottom), or into ash (bath surface). There is no fourth category. If your reconciliation does not close to within 2%, you have a measurement problem, not an efficiency problem.
This is the primary zinc efficiency metric. It captures the cumulative effect of every operational decision made during the period — bath temperature, flux maintenance, immersion times, surface preparation quality, dross and ash management, weighing accuracy. Everything feeds into this one number.
| Consumption % | Status | Likely Cause |
|---|---|---|
| 4.5–5.5% | Excellent | Light-section work or exceptionally well-controlled heavy structural |
| 5.5–7.0% | Normal | Standard mixed structural programme — industry benchmark range |
| 7.0–8.5% | Investigate | Temperature creep, flux iron build-up, or dross removal frequency issue |
| > 8.5% | Action required | Systemic problem — temperature, steel mix change, or weighing error |
The 2024 ASTM revision raised the minimum average coating thickness on structural shapes ≥6.4 mm from 85 μm to 100 μm — an 18% increase in the minimum zinc deposit on heavy sections. For plants supplying ASTM-spec structural work, the benchmark range shifts from 5–7% to 6–8%. The additional zinc is real and correct, not a sign of inefficiency. Confirm which standard governs your contracts and calibrate your benchmark accordingly. Do not penalise operators for correctly meeting a higher specification.
Centrifuge (spinner) plants run total zinc consumption of 5–9% — wider than batch plants because variation by part geometry is significant. The centrifuge action mechanically transfers zinc to the dross zone. This is normal, not a process failure. Track consumption by part category (fasteners vs. brackets vs. bar stock) rather than as a single monthly average — the variation within a spinner plant is too wide for a blended number to be meaningful.
Pickup % tells you what fraction of all zinc consumed actually ended up on the product and is doing its job. It is the complement of the waste percentage. Together they must account for all zinc consumed.
The complement — 25–30% — is accounted for by dross and ash. A pickup % persistently below 65% means the plant is losing too much zinc to waste. A pickup % above 80% should be viewed with scepticism: verify that the outgoing weight measurement is correct and that jig weight is being properly excluded from the incoming steel weight.
| Steel Category | Typical Zinc on Product (% of steel weight) | Notes |
|---|---|---|
| Heavy structural ≥6 mm | 5–7% | Coating-basis metric; 70–75% of zinc consumed on product. ASTM-24 work will be toward upper end. |
| Medium structural 3–6 mm | 4–5.5% | Thinner sections, less zinc per tonne |
| Light structural 1.5–3 mm | 3–4.5% | Sheet and light fabrication |
| Centrifuge — fasteners | 3–6% (variable) | High surface area to mass ratio; centrifuge action increases zinc loss to dross |
Dross is the Fe-Zn intermetallic (approximately 94–96% zinc, 4–6% iron) that accumulates on the kettle bottom as iron dissolves from incoming steel. It is unavoidable. The question is how much of it you produce — and the answer is almost entirely within your control.
| Factor | Effect on Dross Formation | Control Action |
|---|---|---|
| Bath temperature: 450°C → 460°C | Approximately doubles dross rate | Hold at 450°C ±5°C. Log hourly, not just shift-start. |
| Flux iron above 10 g/L FeCl₂ | Direct iron addition to bath every dip | Weekly flux iron test. Regenerate before limit is exceeded. |
| Infrequent dross removal | Dross sitting in kettle consumes bath zinc continuously | Fixed weekly removal schedule — not reactive removal. |
| Over-pickling (rough surface) | Increases iron pickup during immersion | Monitor pickle bath and immersion time — remove steel as soon as clean. |
| Sandelin-range steel (Si 0.04–0.14%) | Higher iron dissolution from reactive steel surface | Check MTC; adjust immersion time; note for monthly reconciliation. |
Dross removal should follow a fixed weekly schedule — not reactive removal when it becomes visible. Plants that remove dross reactively consistently show higher dross percentages and more variable coating quality than plants on a fixed cycle. Before drossing, reduce bath temperature to approximately 440°C to allow the dross-zinc interface to firm up, reducing zinc loss in the removed material.
Ash forms at the bath surface from atmospheric oxidation of molten zinc, flux-zinc reactions when fluxed work enters the bath, and minor amounts of floating dross. Unlike dross, it is a powder with lower zinc content (typically 70–85% recoverable zinc). Its dominant driver is flux — approximately 70–90% of the flux entering the bath ends up in the ash.
The primary ash control lever is flux concentration. Running the flux bath at the lower end of the operating range — 20–25% ZnNH₄Cl rather than 35–45% — significantly reduces ash generation without compromising coating quality, provided flux iron is maintained below 10 g/L FeCl₂. This single adjustment, requiring no capital expenditure, consistently reduces ash generation by 20–35% in plants where flux has been running above the necessary concentration.
Ash must be skimmed from the bath surface before every withdrawal cycle. Ash remaining at the surface when work is withdrawn becomes entrained in the coating — it becomes a surface defect and a zinc loss simultaneously. Skimming takes 30 seconds per cycle. It is never the step to skip when production pressure is high.
This is the financial expression of all four zinc efficiency metrics above. It converts operational performance into the number that matters for pricing and profitability management.
Throughput: 500 MT/month. Zinc consumption: 6.0% = 30,000 kg. Zinc unit cost: SAR 12/kg. Dross: 17% = 5,100 kg × 55% spot = SAR 33,660. Ash: 11% = 3,300 kg × 40% spot = SAR 15,840.
Gross zinc cost: 30,000 × 12 = SAR 360,000. Less recoveries: SAR 49,500. Net zinc cost: SAR 310,500 ÷ 500 MT = SAR 621/MT. This number, tracked monthly, is the clearest measure of zinc efficiency in financial terms.
Every rework batch consumes additional zinc, occupies the kettle for a second cycle, and delays other work in the queue. A first-pass rate of 90% sounds acceptable until you calculate the cost: on a plant running 80 batches per month, 8 rework batches represent an additional partial shift of capacity consumed by work the customer already paid for once.
Thickness compliance rate should be 100%. Not 97%. Not 99%. If batches are being dispatched with readings below the specified minimum — whether ASTM A123/A123M-24 or ISO 1461:2022 — the plant is shipping non-conforming product. The commercial and liability consequences of that are not proportional to the productivity pressure that caused it.
Every zinc cost reduction measure reduces to one of five operational levers. None requires capital investment. All require process discipline applied consistently across every shift, every week. In my experience, a plant that applies all five consistently will find its zinc consumption percentage in the lower half of the 5–7% benchmark — typically 5.0–5.8% — compared to 7–9% for a plant applying none of them. The difference at 500 MT/month is 10–20 MT/month of zinc. At SAR 12/kg, that is SAR 120,000–240,000 per year. From operational discipline alone.
The most common KPI errors in HDG plants are measurement errors, not calculation errors. The formulas are straightforward. The inputs are where most plants fail.
The monthly report is written for management. The plant floor needs something different: a daily visible display that tells operators exactly where the plant stands against its targets. The most effective version I have implemented is a physical whiteboard — not a digital screen, not a printout on a notice board. A whiteboard, updated every shift by the supervisor, showing five numbers.
These five numbers, visible to every operator as they walk in, do more for operational discipline than any management meeting. The operators who understand these numbers — not just read them — consistently outperform those who process steel without any sense of the metrics behind it.
The mechanism is straightforward: when the operator knows that his shift's zinc efficiency number goes on that board, he is more careful about temperature control, ash skimming timing, and whether the thermocouple reading at 14:00 matches the thermocouple reading at 10:00. The KPI becomes personal, not abstract.
When I first structured the full KPI framework across my three plants, the most revealing early result was not about zinc consumption or throughput. It was about measurement consistency.
In the first month of running the complete framework, Plant 2's zinc consumption came out at 6.1% — exactly where I expected it. Plant 1's came out at 9.3% — which I did not expect. The plant had been operating profitably for years. No one had flagged a problem.
The investigation took three weeks. The cause was not a process failure. It was a weighing system problem: jig weight had been included in the incoming steel weight for years, systematically understating the steel processed and therefore overstating the zinc consumption percentage. When corrected, the real consumption was 6.4% — within the normal range.
The lesson: a high zinc consumption number is a starting point for investigation, not a verdict. Before you change your process, verify your measurement. Most apparent efficiency problems are measurement problems in disguise.
