Metallurgical process modelling and simulation consulting services

Metallurgical process simulation use of mathematical models that replicate the behaviour of a mineral processing or hydrometallurgical beneficiation circuit.

These models describe how materials flow through unit operations – crushers, grinding mills, classifiers, flotation cells, leach reactors, thickeners – and how each operation transforms feed characteristics into products, residues, and tailings.

Model parameters are calibrated against measured plant or testwork data so that the simulation reflects real process behaviour, not theoretical ideal performance.

Simulation is needed whenever decisions carry technical or financial risk that cannot be resolved by operating data or testwork alone. Typical situations include feasibility studies and engineering design projects, flowsheet comparison and validation, equipment sizing for comminution and separation circuits, scenario analysis for ore zone transitions or changing feed blends, and recovery optimisation where circuit interactions prevent identification of the best operating strategy from plant trials alone.

A mass balance is a static accounting exercise: it checks that inputs equal outputs across a defined system boundary at a given operating point, producing a reconciled performance picture for a specific set of conditions.

Process simulation goes further. It incorporates the physical and chemical behaviour of each unit operation and predicts how the circuit will respond to changes in feed characteristics, grind size, ore mineralogy, operating conditions, or equipment configuration. It answers ‘what will happen if…?’ across conditions not yet tested.

At CASPEO, simulation and mass balance are complementary and sequential: BILCO data reconciliation provides the verified, internally consistent plant data that calibrates and validates simulation models built in USIM PAC. A simulation model built without a reconciled mass balance as its foundation is built on unverified assumptions.

These three disciplines form a single, integrated framework in which the quality of each depends directly on the quality of the one before it.

Sampling determines whether survey data genuinely represents circuit conditions across the full range of ore types and operating states.

Mass balance reconciliation transforms measured data into a coherent, uncertainty-quantified performance picture, correcting for measurement noise and ensuring internal consistency.

Process simulation uses calibrated models – validated against reconciled survey data – to predict how the circuit will respond to changes not yet made, including ore zone transitions, grind size modifications, reagent strategy changes, and flowsheet reconfigurations.

Investing in simulation without first ensuring sampling quality and reconciliation rigour is a risk. CASPEO’s integrated capability spanning all three disciplines within a single team. Our simulation studies are grounded in data that has been independently verified before a single model parameter is fitted.

At a minimum, a reliable beneficiation circuit model requires: feed characterisation data including particle size distribution, mineralogy, liberation analysis, head grade, and ore hardness; a complete process flowsheet with unit operation parameters; equipment specifications; and measured performance data from plant surveys, pilot plant tests, or laboratory testwork.

For operating plants, representative plant survey data reconciled against a steady-state mass balance is the most critical input. For greenfield projects, simulation models are built progressively as testwork data improves, with ore characterisation (mineralogy, grindability, flotation kinetics, leach behaviour…) providing the foundation at each study stage.

Yes, and this is one of its most valuable applications. At the feasibility stage, simulation models are built from laboratory and pilot testwork data combined with engineering assumptions about equipment selection and operating conditions.

They allow project teams to forecast metallurgical recovery and product grade across different ore types and ore zones, size comminution and separation equipment against design requirements, compare alternative flowsheet configurations on a consistent quantitative basis, and stress-test financial models with sensitivity analyses grounded in process behaviour rather than point estimates.

CASPEO works closely with project teams to assess testwork data quality and identify gaps in ore characterisation that could compromise the reliability of performance forecasts.

USIM PAC is CASPEO’s purpose-built process modelling and simulation software for mineral processing and hydrometallurgical beneficiation operations. Developed and continuously improved over more than 30 years, it covers the full range of unit operations across the mine-to-metal value chain – from comminution and classification through flotation, leaching, solvent extraction, and solid-liquid separation. USIM PAC is recognised in peer-reviewed mineral processing research as a reference simulation platform for beneficiation circuit modelling.
CASPEO’s consulting team uses USIM PAC as the technical engine for all simulation studies. USIM PAC is also available as a standalone software licence for in-house engineering teams seeking to build and maintain their own simulation capability.

▶️ This article could interest you

González M., Brochot S. (2018) – Development of a SAG mill model based on the SAG design test: application to plant design and optimization. Proceedings of IMPC 2018, the XXIX International Mineral Processing Congress Proceedings, Moscow, Russie, Paper ID 587, pp. 1-9.
https://onemine.org/documents/development-of-a-sag-mill-model-based-on-the-sagdesign-test-application-to-plant-design-and-optimization

Yes. CASPEO’s simulation expertise covers hydrometallurgical process routes in full, including heap and tank leaching kinetics, solvent extraction and electrowinning, ion exchange and precipitation, impurity rejection, and solution purification.

For polymetallic deposits, complex or refractory ores, and secondary materials, where process routes combine physical beneficiation with chemical treatment, CASPEO models the full integrated flowsheet within a single simulation environment, capturing inter-stage interactions that would be missed if physical separation and hydrometallurgical stages were modelled independently.

Plant data describes what has happened under past conditions and a specific ore type. It cannot predict how the circuit will behave under different ore zones, after equipment changes, or at different throughputs.

A simulation study is necessary when:

• ore zone transitions are approaching and their impact on grind size requirements, mineral liberation, recovery, and concentrate quality needs quantifying before they reach the plant
• a capital decision is approaching; reconciliation gaps persist despite good data quality
• optimisation through plant trials has plateaued
• a feasibility study requires performance forecasts across a range of ore types that testwork data alone cannot cover

Every model is accompanied by a technical report documenting model structure, calibration data, ore characterisation assumptions, and the limits of applicability including the ore types and operating conditions for which predictions are reliable.

CASPEO works alongside client engineering teams throughout so that the people who will use and maintain the model understand how it was built and where its boundaries lie. For teams wishing to develop in-house simulation capability, USIM PAC training covers model building, calibration, and scenario analysis, allowing clients to update models independently as ore zones change or the flowsheet evolves.

Simulation connects sustainability metrics directly to operating decisions making it possible to evaluate trade-offs, set realistic targets, and demonstrate progress with a transparent technical basis.

CASPEO uses simulation to model water circuits and reuse strategies, comminution energy consumption as the dominant operating energy cost, reagent usage and environmental releases across variable ore types, tailings behaviour and deposition characteristics for closure planning, and circular economy opportunities including secondary material reprocessing. Every sustainability figure is grounded in the same calibrated beneficiation model used for metallurgical performance.