TOOLS
Engineering tools for ore sorting — independent, model-based and built on published methodology
Ore sorting is one of the few unit processes in mineral processing without a widely available, openly published toolset for scoping, sizing and performance estimation. Flotation has JKSimFloat. Comminution has JKSimMet. Ore sorting has, until recently, had little in the way of transparent, physically grounded tools that a project team can pick up and run themselves - to test an idea, size a circuit and understand the numbers without waiting on a third party.
ROKKSTA is developing a suite of open engineering tools for ore sorting, built on physically grounded, first-principles models. These tools are designed for use at scoping and pre-feasibility stage - to test feasibility, size equipment, estimate compressed air and mass balance and understand the performance sensitivity of a proposed ore sorting circuit before committing to physical test work or capital expenditure.
The tools are free to use. The methodology behind them is published and open to peer review. And they apply to any sensor-based ore sorting circuit, regardless of the equipment you ultimately select.
- ROKKSTA Sizing Tool
Size a sensor-based ore sorting installation - mass balance, compressed air and performance curves - in minutes
Disclaimer
The ROKKSTA Sizing Tool is an engineering estimation tool. Outputs are calculated from physics-based models and represent pre-feasibility level estimates only. All tool outputs should be validated against physical sortability trials before any capital expenditure, equipment procurement or process commitment is made. Model accuracy is aligned with the confidence levels appropriate for scoping and pre-feasibility study purposes (approximately ±25–50%). The tool does not replace sortability testing, sensor amenability evaluation or equipment performance guarantees. ROKKSTA accepts no liability for decisions made on the basis of tool outputs alone.
Particle Size Distribution
What the Tool Does
The ROKKSTA Sizing Tool is a web-based engineering application for sizing sensor-based ore sorting installations. Starting from feed material properties and a target operating scenario, it calculates mass balance, compressed air requirements, sorter capacity and key performance indicators - and outputs interactive charts and a print-ready PDF report.
It is the practical implementation of ROKKSTA's published methodology for predicting single-particle ore sorting performance, presented at Physical Separation '26. The underlying model is built from first principles - the physics of particle ejection, belt transport and sensor classification - rather than fitted to any single machine platform, so it applies across sensor-based ore sorting installations.
Who It Is For
The tool is designed for mining engineers, metallurgists, and process engineers who need to:
• Quickly assess whether an ore sorting circuit is feasible for a given ore and target throughput at scoping level
• Generate a preliminary mass balance and equipment sizing estimate for pre-feasibility study input
• Understand how ore sorting performance varies with feed rate, ejection rate, and particle size distribution
• Produce a documented, printable calculation record for internal review or study reporting
Features
Full Rosin-Rammler curve fitting with up to seven anchor points (F100, F95, F80, F50, F20, F5, F0). Enter the sieve data you have - the tool fits the remaining points automatically. The PSD is the foundation of all capacity and performance calculations.
Material Database
Thirty-plus pre-loaded ore densities covering gold, copper, iron ore, zinc, lithium/spodumene, and other common ore sorting commodities. A manual override allows any bulk or particle density to be entered directly for materials not in the database.
Ejection Module Selection
A range of ejection modules - each with size-appropriate valves and pre-populated timing parameters - can be selected from a dropdown. For non-standard configurations, a custom override allows manual entry of ejection module parameters. Ejection module selection directly influences compressed air sizing and mechanical separation performance calculations.
Mass Balance
Concentrate and tailings stream calculations consistently labeled regardless of whether gangue or mineral is the ejection target. Outputs include feed, concentrate, and tailings mass flows, grades, and mass pull fractions.
Compressed Air Sizing
Full compressed air requirement calculation: net air consumption, design contingency (configurable air design factor), flush air allowance where applicable, and a complete pressure breakdown in Nm³/min, cfm, bar, psi, and kPa. Sized to the full working width and operating feed rate.
Interactive Performance Charts
Three visualisations update in real time as inputs change:
• Particle Size Distribution - cumulative passing and histogram, confirming the Rosin-Rammler fit against the entered anchor points
• Total Process Effectiveness vs. Ejection Rate - performance curves for three feed rate scenarios, showing how ore sorting effectiveness degrades as ejection rate and feed rate increase
• Ejection Accuracy and False Ejection Rate vs. Particle Size - per-size-class breakdown of mechanical separation performance, identifying which size fractions are limiting overall effectiveness
Print to PDF / CSV Export
A built-in print layout generates a clean, professional calculation report containing project metadata, all inputs, all outputs, performance charts and the ROKKSTA engineering disclaimer. Suitable for inclusion in study reports and internal technical reviews. An additional .csv export function allows interfacing with other simulation tools.
Methodology
The ROKKSTA Sizing Tool implements the performance prediction methodology described in:
- Riedel, F. & Harbeck, H.: A Method for Predicting the Performance of Single Particle Sorters. Physical Separation '26, Cape Town, South Africa
The method quantifies Total Process Effectiveness (TPE) as a function of ejection accuracy and false ejection rate, both calculated from feed material parameters and sorter design parameters across the full particle size distribution. It is the first openly published upscaling method for single-particle ore sorting at pre-feasibility level and is designed to provide the same class of semi-empirical estimation capability that the JKSimMet and JKSimFloat tools provide for comminution and flotation.
Further detail on the methodology, its assumptions and its validation against physical trial data is available in the published paper.
- Coming Soon
ROKKSTA is developing two further engineering tools that will extend independent ore sorting analytical capability into sensor selection and sample planning.
ROKKSTA XRT Tool
For: Mining engineers and metallurgists evaluating XRT ore sorting feasibility
What it will do: The ROKKSTA XRT Tool predicts the amenability of materials and ores to Dual Energy X-Ray Transmission (DE-XRT) sorting by simulating X-ray attenuation through particles of defined mineralogy and density. Starting from mineralogical data - mineral phases, their proportions and their known X-ray attenuation coefficients - the tool calculates the expected XRT signal response distribution for ore and waste particle populations and predicts the theoretical separation achievable by DE-XRT sorting.
For ore types where XRT is a candidate sensor principle - silicate–carbonate systems, sulphide ores, dense media separation - this tool provides a rapid first-pass assessment of XRT amenability without requiring physical sensor testing. It is designed to sit upstream of sensor amenability testing, providing the quantitative basis for a sensor principle decision before samples are shipped to a test facility.
Status: In development - register your interest below to be notified on release.
ROKKSTA Sampling Tool
For: Project teams designing ore sorting test programmes and variability studies
What it will do: The ROKKSTA Sampling Tool implements Pierre Gy's Theory of Sampling for ore sorting applications. It generates sampling nomograms and calculates the minimum sample mass required to achieve a specified sampling error for a given ore type, particle size and mineralogical composition.
Sampling is the most frequently underestimated source of error in ore sorting evaluations. Test programmes conducted on non-representative samples produce results that cannot be reliably extrapolated to plant scale - and the gap between test sample and ROM material is one of the primary causes of the performance shortfall that many ore sorting installations experience after commissioning. The ROKKSTA Sampling Tool makes correct sample mass calculation accessible at the test planning stage, before samples are collected and before the budget is committed.
Status: In development - register your interest below to be notified on release.
- Why These Tools Exist
Ore sorting sits in an unusual position in the mineral processing toolkit. The technology has been commercially available for decades, but it has never developed the openly available analytical infrastructure that supports confident adoption of other unit processes. There is no widely used, published upscaling standard. There is no established open simulation environment. As a result, project teams often have less ability to model and stress-test an ore sorting circuit themselves than they do for comminution, flotation or gravity separation - which increases project risk and slows the broader adoption of ore sorting as a standard pre-concentration tool.
ROKKSTA's tool development programme is a direct response to this gap. By publishing the underlying methodology and making the tools freely available, we aim to give project teams the same ability to scope, size and stress-test an ore sorting circuit themselves that they already have for every other major mineral processing unit operation.
These tools are a complement to physical test work, not a replacement for it. They are designed to make the period before physical testing more productive - defining what questions the tests need to answer, what sample masses are required and what performance levels justify the investment - and to make the period after testing more rigorous, by providing a quantified framework against which test results can be evaluated.
