Rendering & cold-chain network siting · multi-criteria suitability for the meat-processing industry
Guide
Data
Suitability
Optimizer
Scenarios
What is MCA?
MCA = Multi-Criteria Analysis. It's a structured way to make a decision when several competing factors matter at once and no single number captures “best”. You list the criteria, decide how much each one matters (the weights), score every option against each criterion, then combine those into one overall score so the options can be ranked.
Here the criteria are supply, transport, water, labour and land cost; the “options” are every location on the map; and the weighted combination becomes the suitability heatmap.
What this tool does
MeatChain MCA helps you decide where to put meat-industry facilities. It does two linked jobs:
1 · Suitability mapping Blends weighted criteria (livestock supply, transport, water, labour, land cost) into a single colour map showing how suitable each location is.
2 · Network optimisation Places a chosen number of rendering / cold-storage / depot hubs to minimise volume-weighted haulage from your plants.
Quick start
Pick a region & load plants. Open the Data tab, choose Australia, New Zealand or Australasia, then explore the sample plants or Download Excel template → fill it in → Upload plants.
Set what matters. On the Suitability tab, drag the weight sliders — or use AHP to answer “which matters more?” questions and have the weights calculated for you.
Place the hubs. On the Optimizer tab, pick a facility type and how many hubs, then Optimise network. Export the result to Excel.
Compare options. Use the Scenarios tab to save two setups (e.g. transport-led vs water-led) and compare them side by side.
The tabs
DataChoose the region (Australia / New Zealand / Australasia), download the template or upload your plant list, edit throughput and type inline, group by operator (e.g. open or close all JBS sites at once), and run what-if changes — close, reopen, remove, or add sites. Everything recalculates from the active sites.
SuitabilityCriteria weights, AHP guided weighting, the colour scheme, and the live suitability heatmap.
OptimizerChoose facility type and hub count; solve optimal locations; read total haulage and per-hub catchments. Then use Cost comparison to price the network in dollars and pit your own-build hubs against third-party providers (transport + gate fee + fixed cost). Export either to Excel.
ScenariosSave / load / compare two complete setups, with the haulage difference between them.
Reading the map
The heatmap runs blue (low suitability) → red (high), recoloured by your chosen scheme. Dots are processing plants — colour shows type, size shows throughput. Numbered squares are optimised hubs, with lines to the plants each one serves.
Where the criteria data comes from
Important: each criterion is a transparent geographic proxy computed live in your browser — not an ingested authoritative dataset. They're built for exploring trade-offs, not for final decisions. Here's exactly what drives each one:
Livestock supplyVolume-weighted closeness to the processing plants in your list (plants sit near their supply). Source: the plant list itself — the sample data, or whatever you upload. Not a livestock-density dataset.
Transport accessCloseness to a built-in list of major cities, weighted by population, for road and metro-market access. Source: ~12 built-in reference points per region. Straight-line, not a road network.
WaterCloseness to a built-in set of high-rainfall / coastal anchor points — a coarse stand-in for water availability. Source: built-in coastal/high-rainfall anchors. Not BOM / NIWA rainfall, river or water-allocation data.
LabourCloseness to population centres (the same city list, population-weighted) as a stand-in for workforce access. Source: built-in city populations. Not census or employment data.
Land costDistance from the biggest cities — cheaper and better-buffered further out, peaking around 190 km. Source: derived from the city list. Not land-valuation or zoning data.
Export portsNow has its own weight slider on the Suitability tab — turn it up for export-heavy operations. It scores closeness to major export seaports (Brisbane, Melbourne, Tauranga, Bluff, etc.), weighted toward bigger ports, separately from general transport. Source: the port-flagged reference points. There's not yet a hub→port shipping leg in the optimiser/cost.
To make this decision-grade, each proxy can be swapped for a real layer: ABS / Stats NZ population & employment, BOM / NIWA rainfall and water-allocation, real road travel times, and land-valuation / zoning data. Ask and I can wire in a real dataset where it matters most.
How the numbers are calculated
DistanceStraight-line (great-circle) between points. Real road distance is typically 1.2–1.4× longer, so treat distances and costs as directional, not exact.
SuitabilityEach criterion is scored 0–1 across a grid, blended using your weights (auto-normalised so only their relative sizes matter), then re-scaled 0–1 for colour contrast.
OptimiserA throughput-weighted k-means places the hubs to minimise total volume-weighted haulage (tonne-km) from every active plant to its nearest hub.
CostTotal landed = transport ($/t·km × tonne-km) + gate fee ($/t × tonnes) + fixed cost ($/yr ÷ 52) for each hub that's actually used. Each plant routes to the cheapest included hub.
TemperatureChilled / frozen set default freight and gate-fee rates and a maximum-haul guideline; hubs whose longest haul exceeds it are flagged.
Good to know
Hover almost any control, label or metric for a tooltip explaining it. The plant throughputs are illustrative placeholders, not published figures — edit them on the Data tab or upload your real numbers. Plant locations are grounded against operators' official site lists. Always validate against real volumes, road networks and zoning before any decision. Uploaded spreadsheets are read inside your browser and never sent anywhere.
Criteria weights
25
Closeness to cattle/sheep supply & existing kill floors.
20
Proximity to highways and metro markets.
15
Closeness to a major export seaport (Brisbane, Melbourne, Tauranga, Bluff …).
15
Processing & rendering are water-intensive.
15
Access to a regional workforce.
10
Cheaper land set back from cities (odour/effluent buffer).
AHP weighting guided
Not sure what numbers to put on the sliders? Compare the criteria two at a time and AHP works out the weights for you, then fills the sliders above (still adjustable). In each row the two criterion names sit left and right — pick a button: ≫ left matters much more, > left a bit more, = equal, < right a bit more, ≪ right much more. Hover a name or button for plain English.
Colour scheme
Display
Facility to place
Chilled / frozen set freight & gate-fee defaults and flag hubs whose haul exceeds the safe range.
3
Solver places this many facilities to minimise volume-weighted haulage from every plant to its nearest hub.
Network result
Total haulage
—
'000 tonne-km / wk
Avg distance
—
km, volume-wtd
Hubs placed
—
facilities
Throughput
—
t / week
Cost comparison $
Turn the network into dollars. List hub options — your own-build hubs and/or third-party providers — and each active plant is routed to whichever included option is cheapest on transport + gate fee. Fixed cost is charged only to hubs that actually get used.
$ / t·km
Transport
—
$'000 / wk
Gate fees
—
$'000 / wk
Fixed
—
$'000 / wk
Total landed
—
$'000 / wk
Region
Sets the map, the sample plants, and the city / port / water reference layers behind the suitability surface. Pick the region your uploaded data belongs to (use Australasia for trans-Tasman networks).
Plant data
The map, heatmap and optimiser all read from one plant list. Download the Excel template, fill it in (instructions are on the second sheet), then upload it here to replace the sample data.
Loaded: 21 sample plants (illustrative).
Add / close sites what-if
Model closures and acquisitions: untick a site to close it, tick to reopen, ✕ to remove it for good, or add a new / acquired site below. The map, heatmap and optimiser update from the active sites only.
Current sites
Tick/untick to open or close a site · t/wk and type are editable · ✕ removes.
Scenario compare two-way
Save the current weighting + hub setup as a scenario, change the weights, save another, then compare their optimal networks side by side.