Process-Based Techno-Economic Assessment in Mining
Jan 27, 2026
A Practical Framework for Evaluating Emerging Technologies
Mining companies are under increasing pressure to reduce cost, risk, and environmental impact across mining, processing, and closure activities. At the same time, a growing number of emerging technologies promise improved sustainability outcomes, offer resource recovery pathways, or provide opportunities to commercialise by-products.
Mining companies are not short on sourcing innovation, but they do struggle with decision velocity. Decision evaluation presents a bottleneck when evaluating early-stage technologies in the innovation pipeline, and early-stage ventures may end up dead in the water if it takes too long for heavy asset owners to decide on whether to invest.
This article presents a process-based techno-economic assessment (TEA) framework designed to support early-stage decision making when data is limited, uncertainty is high, and a variety of deployment options must be considered.
Why Traditional Assessments Break Down in Mining
Technology assessments in mining are typically delivered as consultant-led engineering studies. This approach works well for mature assets and established processes, where design specifications are well defined. But it can be much less effective when applied to low- to mid-technology readiness level (TRL) technologies, where:
A lack of prior art makes scale-up modelling research-intensive.
Design specifications are incomplete, meaning high-fidelity modelling tools cannot be used.
Site-specific considerations drive technology adoption more than product capabilities.
Value assessment extends beyond cost estimation and needs to consider future cash flows.
Due to these challenges, bespoke effort is usually required to construct models of early-stage technologies. It may also fall on the innovator to present the initial TEA of their solution to an asset owner, leading to an elaborate dance between site-based personnel, consulting engineers, finance teams, and the technology vendor.
A lack of transparency and standardisation leads to repeated work, while feedback loops cause valuations to take months to complete. This impacts the innovation pipeline via expensive consulting fees, missing investment windows, or restricted deal flow. Start-ups may run out of runway before a decision is reached, and asset owners can lose millions on investments that are ultimately not feasible in the long-term.
What “Process-Based” Techno-Economic Assessment Means
R&D engineers often struggle with conflicting performance objectives between business-as-usual operating envelopes and emerging technologies. This can be as extreme as the success of one technology directly causing the failure of another process in the value chain. For example, optimising for product A can increase the cost of feedstock B, and the net result can be a reduction in performance for both procurement and commercial teams.
Innovation managers are often faced with a series of claims made by solution providers. How does one quantify the net impact of deploying 5 or 10 different solutions in the value chain that each promise a 20% improvement? This is difficult as performance improvements are not multiplicative or additive; they require an understanding of system dynamics.
Process-based TEA shifts the focus from isolated technology assessments to flowsheet-driven system evaluation. Developing process models enables multiple deployment options to be considered. Rather than treating technologies as standalone units, this approach can model how technologies will:
Interact with upstream and downstream processes (quality, throughput).
Integrate with existing and planned infrastructure (upgrades, studies).
Influence system-wide mass balances, operating cost models, and process economics.
These factors enable site-based evaluations and asset owners to incorporate system dynamics when making investment decisions.
Site-Based Technology Evaluations
A critical requirement of assessing technologies in heavy industries is performing a site-based evaluation. Without adjusting to the specific needs of a site, emerging technologies cannot be successfully adopted. As technologies rarely operate in isolation, their value depends on how they interact with:
Existing engineering systems.
Planned upgrades.
Site-specific chemistry and material flow models.
The energy supply mix.
Other operational constraints.
By embedding technologies into site-representative process models, decision makers and innovators can carefully match site data with product capabilities.
Embedding Economics Early in Technology Decisions
While traditional studies often reduce valuation to a cost-estimation exercise, resource recovery pathways require similar focus on value creation. This may require considering alternative business models to drive commercialisation.
Process-based TEA integrates decision evaluation with techno-financial considerations. This involves:
Using consistent economic criteria (e.g. NPV, ROI) across options
Explicitly considering revenue and future cash-flow in models
Testing sensitivity to key variables such as pricing, scale, and operating conditions
This ensures early-stage assessments readily translate into investment decisions, rather than running engineering and financial models as separate work streams.
Example: Evaluating Mine Water Remediation Technologies
The evaluation challenge is commonly faced by Tier-1 operators. This framework was recently applied to evaluate emerging technologies for mine-impacted water at a large-scale base metals site.
The objective was to screen multiple deployment pathways, assess system-level interactions with existing infrastructure, and evaluate economic performance under a range of assumptions.
Using a process-based TEA approach enabled the following outcomes for the client:
Comparison of multiple technology configurations.
Integration with existing and planned treatment systems.
Sensitivity analysis on key commercial and operating drivers.
Transparent collaboration between technical and commercial stakeholders.
The result was improved decision evaluation and communication, enabling faster decisions and deferring the need for high-resolution studies.
The Place for Process-Based TEA in Engineering and Finance
In practice, process-based TEA complements—rather than replaces—later-stage engineering studies and financial modelling. This ensures that engineering design expenditure is reserved for projects at an appropriate maturity level, and ensure early-stage decisions incorporate financial metrics from the start.
Process-based TEA is best suited for:
Early-stage or emerging technologies.
Situations with limited design data.
Option screening and portfolio evaluation.
Decisions involving system-level trade-offs.
It is important to note that TEA alone cannot take the place of investment due diligence or engineering design. However, by conducting process-based TEA, early-stage decisions can be made at a fraction of the cost, while detailed modelling and analysis are reserved for more mature, market-ready solutions.
Common Failure Modes in Early-Stage Technology Evaluation
Some of the common missteps made in TEA include:
Failing to incorporate economies of scale. The price of chemicals in the lab is often orders of magnitude different from bulk cost.
Poor equipment selection. The capital cost of equipment dilutes with scale unless custom equipment manufacturing is required. Choosing to manufacture something bespoke rather than making use of a combination of available technologies can massively increase cost.
Evaluating technologies in isolation from site context–for example, choosing an arbitrary scale rather than working to a customer’s needs. For mining ventures that adopt a platform approach, this might involve choosing topical commodities rather than adapting to a specific customer’s immediate problem or need.
Recognising these failure modes is as important for founders as it is for deal analysts in ensuring emerging technologies can be successfully commercialised.
Why This Framework Matters
As mining companies evaluate an increasing number of emerging technologies—particularly for water treatment, decarbonisation, and critical minerals initiatives—the ability to make early, defensible decisions becomes increasingly critical.
Process-based techno-economic assessments provide a scalable, system-level solution, supporting faster innovation cycles and improving decision evaluation and communication.
As climate and resource recovery technologies accelerate toward net-zero targets, frameworks that shorten decision cycles will increasingly determine which innovations can be successfully commercialised.
About Lewi
Lewi develops process-based techno-economic models that help mining companies and technology vendors align engineering and financial models and accelerate early-stage decision making.
