Recent Project Updates — The Integrated Platform in Action (Anonymised)

These are anonymised summaries of recent IMC projects. Client identities, locations, asset and pit names, customers and commercially sensitive figures have been removed or generalised; any figures shown are indicative.

One platform, every commodity

IMC works across the commodity spectrum — gold, copper, nickel, diamonds, iron and polymetallic deposits. The same integrated platform adapts to each because the physics, the optimisation mathematics and the financial logic are universal; only the flowsheet, the recovery curves and the fiscal regime change.

Project A — Copper–Gold Porphyry (PFS)

A copper–gold porphyry carrying magnetite and silver by-product credits, taken through a pre-feasibility-level study.

• Integrated block-model manipulation — reblocking, sub-blocking, re-domaining and field transforms all performed inside the platform, so a change propagated straight through optimisation, scheduling and costing on one consistent, auditable version.
• Pseudo-flow optimisation — pit shells generated with IMC’s own HPF optimiser.
• Project-specific NSR and recovery — a copper concentrate-grade log curve and multi-element NSR (copper with gold, silver and magnetite credits), per block.
• Haulage simulation as a cost driver — haulage, a primary operating cost, modelled with first-principles simulation and fed directly into the MineCost cost model.
• Zero-based cost — carried operating and capital costs through to economics.
• Enterprise financial model for investor review — the costed schedule flowed into a full enterprise financial model (three statements, fiscal regime, debt and Bayesian, correlated risk analysis), investor-ready, with workbook output structured to the FAST and Modano conventions.

Why it matters. A single environment took the project from drillholes all the way to a fully costed enterprise financial model with Bayesian risk, ready for investor review — every block-model change, optimisation shell and cost flowing through one consistent, auditable model.

Project B — Copper–Cobalt Project with By-Product Credits (FS)

A copper project with cobalt, silver and magnetite by-product credits, at feasibility-study level.

• Pseudo-flow optimisation and direct block scheduling — in-house — the pit was optimised with IMC’s own HPF engine and the extraction sequenced with IMC’s direct block scheduling (DBS), run end-to-end within the platform.
• Sophisticated recovery modelling — copper recovery modelled with a feasibility-grade polynomial in copper grade adjusted by the copper soluble-acid ratio (CuSA).
• By-product credit sensitivities — clean scenario testing of the credits (adding/removing silver and magnetite, flexing the magnetite price) with NSR and recovery re-applied each time.
• Cost to finance — zero-based costs flowed into the enterprise financial model, with output structured to the FAST and Modano conventions.

Why it matters. Polymetallic economics live or die on the by-product assumptions. Because recovery and NSR are computed per block and re-run on demand, the team could test “what is this credit actually worth?” rigorously, rather than guessing with a flat factor.

Project C — Lateritic Nickel Direct-Shipping-Ore Operation

A lateritic nickel direct-shipping-ore (DSO) operation supplying multiple customers at different nickel-grade specifications.

• Haulage simulation as the primary cost driver — route-by-route haulage modelled with first-principles simulation and integrated directly into the MineCost cost model.
• Multi-pit, multi-material, multi-customer scheduling — full Minemax integration — the allocation was a complex MILP problem (several pits; ore categories of economic ore, sub-economic ore and high-iron material; and distinct customers each with their own target nickel grade), so IMC integrated fully with Minemax for the detailed MILP, with the platform preparing and refining the physics-costed inputs it ran on.
• Scenario throughput cases — two production cases, a lower and a higher plant-feed rate, scheduled and compared over a multi-year horizon, with waste / ore-to-product splits resolved per pit and per year.
• Heavy reconciliation and QA — verifying tonnes, grades and material splits against the client’s own figures, pit by pit, grade by grade, customer by customer.

Why it matters. DSO operations are an allocation problem — the right material, to the right customer, at the right spec, in the right period. Doing that across many pits and products, and reconciling it back to the client’s numbers, is exactly where an integrated, transparent platform earns its keep.