For many Brazil ranches and feedlots, steam-flaked corn sits at the center of two competing pressures: it’s a valuable energy component in rations, but it can also be a persistent cost and logistics headache. If you’re weighing whether to keep buying flakes or produce them on-site, the decision is less about a single “price per ton” and more about how stable your supply chain and operating costs will be over the next 12–24 months.
This guide walks you through a practical “buy vs. make” framework, then shows how to stress-test your model under Brazil electricity conditions—including the surcharge impact that can appear under different generation scenarios.
1) Start with demand: the number that drives everything
Use one formula to anchor the rest of your model:
Daily flake demand (tons/day) = (Headcount × kg/head/day) ÷ 1,000
Example:
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5,000 head × 5 kg/head/day = 25 tons/day
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Annual volume ≈ 9,125 tons/year
Even if your operation is smaller, the same logic applies. The more consistent your daily consumption, the easier it is to justify process control and reduce delivered-feed risk.
2) External purchase: don’t compare “prices,” compare cost drivers
Delivered steam-flaked corn typically bundles several cost layers:
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Processing (flaking service and quality control)
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Logistics & handling (distance, unloading, scheduling, shrink)
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Supplier margin (risk, financing, service level)
That means two suppliers can quote the “same” ton price while delivering very different realities—different moisture specs, different shrink assumptions, different delivery reliability, and different penalty clauses.
When you request quotes, ask for the assumptions behind the number:
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Delivery distance, minimum order, and delivery frequency
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Moisture/spec penalties and how they’re measured
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Typical shrinkage and who bears the loss
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Seasonal adjustment terms (if any)
If your current supply is dependable and the delivered cost is stable, external purchase can be the simplest choice. But if your operation regularly feels the pain of delayed trucks, inconsistent spec, or volatile pricing, it’s worth modeling the “make” option seriously.
3) In-house production: the cost structure you can control
On-site flaking cost is usually driven by:
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Electricity (rollers, conveyors, auxiliaries)
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Steam fuel + water (conditioning)
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Labor + maintenance + wear parts
As a reference, integrated flaking systems are designed to simplify the on-ranch workflow—reducing handling steps and making it easier to align conditioning, flaking, and downstream logistics. When you evaluate a system, focus on the parts that determine real-world operating cost and uptime: stable throughput, access for maintenance, wear-part planning, and utilities consumption per ton.
For a concrete view of what “integrated” typically means in practice, see this overview of a steam-flaked corn production line:
Steam-Flaked Corn Production Line
4) Brazil electricity: a clean plug-in (including “flag” surcharges)
Electricity in Brazil varies by state, distributor, and tariff class. Some market references around mid-2025 commonly cite averages roughly in the range of:
Some forecasts also point to upward pressure from sector charges and budget adjustments, so it’s wise to test a conservative scenario rather than assuming flat tariffs.
Step A — Convert kWh/ton into cost/ton
If your flaking line consumes about 17.5 kWh/ton (a common modeling value for a ~2 t/h line at moderate effective load):
Step B — Add “flag” surcharge when applicable
Brazil’s “flag” mechanism can add a surcharge per 100 kWh under tighter generation conditions. Commonly cited surcharge references include:
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Yellow: +1.88 BRL / 100 kWh
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Red 1: +4.46 BRL / 100 kWh
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Red 2: +7.87 BRL / 100 kWh
To translate into your per-ton model:
Example at 17.5 kWh/ton:
In most cases, steam fuel has a bigger impact than electricity flags—but including flags helps you stress-test ROI and avoid “too-optimistic” spreadsheets.
5) Steam and water: often the bigger lever than electricity
A practical conditioning benchmark often used in cost models is:
Your actual steam cost will depend on fuel choice (diesel, gas, biomass, electric), boiler efficiency, and operating discipline (warm-up losses, downtime patterns, maintenance). If your delivered flake price is high, tightening steam efficiency can move your payback faster than chasing marginal electricity savings.
6) Operational value: why “making” can reduce risk (not just cost)
Beyond the per-ton calculation, on-site flaking can improve:
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Supply stability: less exposure to delivery disruptions and scheduling gaps
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Freshness control: shorter storage time and tighter feeding rhythm
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Process integration: easier coordination with handling, storage, and feeding logistics
If you want to connect this decision to a broader feeding workflow (ingredients, processing steps, and on-farm execution), this overview is a helpful reference point:
Animal Feed Solutions
Common pitfalls (and how to avoid them)
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Only modeling electricity, ignoring steam reality → include fuel, boiler efficiency, warm-up time, and downtime.
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Under-planning wear parts → budget rollers/bearings and set inspection intervals.
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Over-sizing capacity → match throughput to your staffing and maintenance capability.
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Skipping raw corn variability → plan for moisture swings and impurities in your operating procedure.
Questions to ask before you commit (copy/paste)
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What are the expected kWh/ton and steam kg/ton under a realistic moisture range?
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What are the typical wear parts and replacement intervals?
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What commissioning support is included (training, ramp-up, documentation)?
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What footprint/height and maintenance access are required for safe operation?
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How will the line integrate with your handling, storage, and feeding workflow?
Next step: turn this into your site-specific worksheet
If you want to move from “concept” to “decision,” build a one-page worksheet that includes: your daily tons, your delivered purchase price range, your electricity tariff class, your steam fuel cost, and a conservative uptime assumption. Once those are in place, the buy-vs-make answer usually becomes obvious—and defensible.
