Process modelling can help inform early Metals & Minerals project decisions, from feasibility studies to footprint analysis, by reducing uncertainty around capital and operating costs, recoveries, and energy efficiency.

However, uncertainty is often highest in the early project phases: feed variability, incomplete test work, competing flowsheet options, and tight schedules can all affect decision-making.

At Sweco, we use process modelling as a practical way to manage this uncertainty. Using tools such as HSC Chemistry (HSC Sim), we develop robust modelling frameworks that support decision-making from concept selection to the engineering basis. Where needed, these models can also support footprint analysis and operational optimisation.

Why process modelling matters—and why “later” is often too late

Process modelling is more than a simulation tool for specialists. It provides a shared engineering language that connects metallurgy, process design, energy, environmental performance, and cost.

When introduced early, process modelling enables teams to test alternatives virtually, identify bottlenecks, and quantify trade-offs before changes become costly. Equipment sizing and energy integration decisions can have a significant impact on CAPEX, OPEX, throughput, and environmental footprint. Early modelling therefore supports more informed design choices and a stronger engineering basis.

What we do with process modelling in HSC

Using HSC Sim, we can represent complex flowsheets by linking unit operations, stream compositions, reactions, and energy balances. This enables us to assess how changes in operating conditions or design parameters affect the overall system.

For clients, process modelling can deliver tangible outcomes such as:

1. Flowsheet option screening and feasibility support

Process modelling enables rapid comparison of alternative processing routes, such as different pre-treatment steps, recycle strategies, impurity-control approaches, or energy concepts. This allows early go/no-go decisions to be based on quantified impacts rather than assumptions.

2. Consistent mass and energy balances

A well-executed modelling approach ensures that mass and energy balances are consistent across the flowsheet. This provides a reliable basis for downstream engineering while keeping assumptions transparent and traceable.

3. A stronger sizing basis and reduced performance risk

Process modelling links process conditions directly to stream data and energy requirements. This strengthens the basis for equipment sizing and reduces the risk of designing for incorrect or unrealistic operating conditions.

4. KPI-driven design and optimisation

Modelling supports KPI-focused engineering. Through sensitivity analyses and scenario comparisons, we can identify the variables that most influence recoveries, grades, energy efficiency, and reagent and energy consumption—as well as the trade-offs between different KPIs.

5. Environmental footprint analysis and LCA readiness

Process modelling can support sustainability analysis by generating data for evaluating emissions, resource use, and energy demand. The results can also feed into life cycle assessment (LCA) workflows, enabling footprint-informed design decisions and helping embed defined sustainability targets into engineering work.

Where process modelling helps most: mining, smelters, battery materials, and recycling

The value of process modelling extends across the Metals & Minerals value chain:

1. Mining and mineral processing: Assess feed variability, recovery–grade trade-offs, and energy intensity.
2. Pyro- and hydrometallurgy: Quantify chemical constraints, impurity behaviour, and the effects of recycle streams.
3. Battery materials and recycling: Compare process routes, assess reagent and energy impacts, and establish traceable design assumptions for permitting and ESG reporting.

Across these applications, process modelling improves decision quality under uncertainty. It makes decisions more transparent, faster to iterate, and easier to justify.

How clients engage with Sweco

Client engagements involving process modelling typically follow one of these patterns:

1. Short screening studies: Rapid evaluation of process options.
2. Feasibility-to-design-basis modelling: Development of mass and energy balances, sizing inputs, and KPIs.
3. Footprint- and LCA-driven engineering: Integration of sustainability targets into process design decisions.
4. Operational improvement: Optimisation of existing plants or support for ramp-up performance.

Case study

In one project, HSC-based process modelling was used to develop mass and energy balances for a pCAM manufacturing process, including the associated wastewater treatment.

1. Scope: Full-process mass and energy balances, with simplified wastewater treatment modelling to link downstream flows with upstream assumptions.
2. Timing: The modelling work was carried out relatively late in the design phase.
3. Value delivered: Even at this stage, process modelling helped confirm utility-sizing assumptions, reduce uncertainty in load estimates, and ensure consistency in the design basis.
4. Client outcome: The client requested the model for future development, and it was delivered as a foundation for ongoing optimisation.

This demonstrates that process modelling is not limited to early-stage studies. It can also create value through late-stage validation and long-term process improvement.

Whether evaluating a new Metals & Minerals project or improving an existing operation, process modelling is a powerful tool for reducing uncertainty, improving design quality, and supporting better decisions.

Are you evaluating process options, developing a feasibility study, or looking to optimise an existing operation? Sweco’s process modelling specialists can help you build a robust, traceable basis for technical, commercial, and sustainability-focused decisions.

Get in touch!

Arezoo Rahmani, Metals and Minerals Specialist, arezoo.rahmani@sweco.fi