- Why Equipment Audits Matter
Ore sorting equipment that was commissioned and performing well does not stay that way without active management. Sensor calibration drifts. Feed characteristics change as the mine advances. Wear accumulates in mechanical components. Threshold settings that were optimised at commissioning become misaligned with the ore actually being processed. The result is a gradual, often invisible erosion of ore sorting performance - lower recovery, higher dilution and reduced economic return - that rarely triggers an obvious alarm before significant value has already been lost.
ROKKSTA's ore sorting equipment audit service provides a structured, evidence-based assessment of whether your ore sorting installation is performing at its potential. We evaluate equipment condition, sensor performance, feed preparation, classification logic and mechanical separation effectiveness as an integrated system - not as isolated components - and translate findings into a quantified picture of where performance losses are occurring and what they are costing.
What gives an audit its value is the method, not a position taken on the equipment market. Every finding is grounded in physical measurement and benchmarked against the intrinsic potential of the ore actually being processed. We do not attribute losses to the ore by default and we do not assume the machine is the problem either - the audit's central task is to determine, from measured data, which it is. Our only objective is an accurate diagnosis and a practical path to improvement.
- Recognising When Performance Has Slipped
Ore sorting underperformance rarely announces itself clearly. The following situations are the most common indicators that an audit is warranted:
Recovery has declined without an obvious cause. Grade and mass balance data show that more ore is going to tailings than expected, but the source of the loss is unclear. This is frequently a sensor calibration issue, a threshold drift or a feed preparation change that has not been formally evaluated.
The ore body has changed. As a mine advances - through different lithologies, depth intervals or ore domains - the material presented to the ore sorter changes with it. An ore sorting system calibrated for one ore type may perform poorly on another without any mechanical fault. Periodic re-characterisation and re-optimisation are essential.
Commissioning performance has not been sustained. Commissioning results represent the best achievable performance under controlled conditions with fresh calibration and ideally prepared feed. Many operations find that real-world performance diverges from commissioning benchmarks within months. An audit identifies where and why.
Ejection rates or mass rejection figures are unexpectedly high or low. Either extreme can indicate a threshold or feed preparation problem that is costing recovery or failing to achieve the intended waste rejection.
A production review, investment decision, or operational change is planned. Before expanding capacity, changing the ore blend, modifying the circuit upstream or downstream of the sorter or committing to a capital investment, a measured performance baseline is essential.
The machine has never been audited since installation. For ore sorting equipment that has been operating for more than 12–18 months without a structured performance review, the probability that at least one significant performance gap exists is high.
- Understanding Ore Sorting Performance: OEE
ROKKSTA structures all ore sorting equipment audits around the Overall Equipment Effectiveness (OEE) framework - a globally recognised manufacturing performance metric adapted specifically to the requirements of sensor-based ore sorting.
OEE quantifies total ore sorting system performance as the product of three independent components:
Availability - the proportion of scheduled operating time during which the ore sorting machine is actually running. Availability losses arise from unplanned breakdowns, excessive maintenance downtime and start-up or changeover delays. For ore sorting equipment, availability is often underreported because minor stoppages are absorbed by buffer stockpiles without triggering formal downtime records.
Performance - the degree to which the ore sorting machine achieves its design throughput during operating time. Performance losses arise from reduced belt speed, sub-optimal feed rates, irregular feed presentation and particle singulation failures that force the machine to operate below its rated capacity.
Quality - the degree to which the ore sorting machine makes correct classification decisions and translates them into accurate physical separation. Quality losses in ore sorting manifest as Type 1 errors (waste particles misclassified as ore, reducing rejection efficiency and contaminating concentrate) and Type 2 errors (ore particles misclassified as waste, reducing mineral recovery and increasing tailings grade).
OEE = Availability × Performance × Quality
In ore sorting operations, Quality losses - driven by sensor calibration drift, threshold misalignment and presentation variability - are frequently the dominant source of underperformance and the least visible in routine production monitoring. They are also the most cost-effective to address.
- What We Assess: Four Root Cause Areas
ROKKSTA's ore sorting equipment audits examine performance losses across four interconnected areas. Understanding which area is the primary driver - and which are contributing factors - is the central diagnostic task of the audit.
1. Sensor Performance and Calibration
The sensor system is the intelligence of any ore sorting machine. Its ability to generate consistent, reliable classification signals depends on correct calibration, stable operating conditions and alignment between the sensor's detection capability and the specific contrast properties of the ore currently being processed.
We assess:
• Sensor signal quality, contrast margins and noise levels relative to the ore being sorted
• Calibration currency and calibration methodology - including whether calibration standards accurately represent the ore's physical and compositional properties
• Threshold settings relative to the current ore feed - identifying whether settings established at commissioning or on a previous ore domain remain appropriate
• Classification logic and image processing parameters - including sensitivity to particle orientation, surface condition and size variation
• Comparison of current sensor response against amenability test baselines where available
Sensor calibration drift is one of the most common and most correctable sources of ore sorting performance loss. In many operations, a calibration review and threshold re-optimisation alone recovers several percentage points of mineral recovery.
2. Feed Preparation and Particle Presentation
The ore sorting machine can only classify particles correctly if they are presented to the sensor in a condition that allows the sensor to do its job. Feed preparation - crushing, screening, washing and feed rate control - and particle presentation - singulation, belt speed and particle orientation - are upstream variables that directly govern what the sensor sees and are frequently the primary limiting factor in ore sorting performance.
We assess:
• Particle size distribution of the actual sorter feed relative to the design operating range
• Feed rate consistency and belt loading (area occupancy) - excessive loading increases particle clustering and co-ejection errors
• Singulation quality and particle spacing on the belt
• Particle orientation effects and their influence on surface-sensing technologies
• Wash water systems where applicable - surface contamination from fines, mud and oxidation products can severely degrade optical and NIR sensor performance
• Upstream screening performance - whether the undersize fraction correctly bypasses the sorter and whether fines contamination in the sorter feed is within acceptable limits
Poor feed presentation can make an otherwise capable ore sorting system appear technically unsuitable for the ore - a misdiagnosis with significant consequences for investment decisions.
3. Mechanical Separation Effectiveness
Once a particle has been correctly classified, the ore sorting machine must physically eject it into the correct stream. The precision and reliability of the pneumatic ejection system - nozzle condition, valve response times, air pressure and splitter position - determines how faithfully classification decisions are translated into physical separation.
We assess:
• Ejection nozzle condition, wear and flow characteristics
• Compressed air pressure, flow rate and consistency across the working width
• Valve response times and energize/de-energize characteristics relative to material transport speed
• Splitter position and geometry relative to the ejection trajectory for the current ore size range
• Co-ejection behaviour - the degree to which adjacent non-target particles are unintentionally deflected along with correctly targeted particles
• Separation sharpness - the precision of the ore/waste boundary under current operating conditions
Mechanical ejection losses are often wrongly attributed to sensor limitations. An audit that correctly separates classification errors from ejection errors provides a much more accurate diagnosis - and a more targeted path to recovery.
4. Process Integration and Operational Factors
Ore sorting performance is not determined solely by the machine itself. The integration of the sorter into the broader process circuit and the operational practices governing its day-to-day use, have a substantial influence on real-world outcomes.
We assess:
• Upstream crusher and screen performance and its impact on sorter feed quality
• Downstream handling of concentrate and tailings streams - including whether misclassified material can be identified and recirculated
• Operator procedures - including threshold adjustment practices, response to feed changes, maintenance scheduling and calibration frequency
• Alignment between ore sorting performance targets and production KPIs
• Benchmarking of current performance against design specifications, performance guarantees and comparable installations in the industry
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- Our Methodology
ROKKSTA's ore sorting equipment audits follow a structured, data-driven methodology that integrates on-site observation with quantitative performance analysis.
1. Pre-Audit Data Review
We review existing production data, calibration records, maintenance logs, feed characterisation data and any available ore sorting test results before arriving on site. This defines the audit scope, identifies the most likely performance gap areas and ensures on-site time is used efficiently.
2. On-Site Inspection and Measurement
We conduct a physical inspection of the ore sorting machine and its feed system under real operating conditions - not during a scheduled maintenance stop. We directly measure feed rates, belt loading, particle size distribution on the belt, air pressure, nozzle condition and sensor signal quality. We observe the full sorting cycle, including ejection behaviour and splitter performance.
3. Performance Testing
Where conditions allow, we conduct targeted sampling of concentrate and tailings streams to generate real-time mass balance, recovery and grade data. We compare measured sorting outcomes against the intrinsic sortability baseline for the current ore feed - establishing the gap between theoretical potential and observed machine performance.
4. Quantitative Analysis
We calculate OEE and its three components, quantify Type 1 and Type 2 error rates, and identify the relative contribution of each root cause area to total performance loss. All findings are supported by measured data, not qualitative observation alone.
5. Root Cause Identification
We link observed performance losses to their specific technical and operational sources, separating material-driven limitations from machine-driven limitations and sensor-driven losses from mechanical ejection losses. This distinction is critical for prioritising corrective actions correctly.
6. Benchmarking
We compare current ore sorting performance against the machine's design specifications, commissioning results, applicable performance guarantees and where applicable, comparable ore sorting installations in the industry.
7. Reporting and Action Plan
We deliver a structured audit report with quantified findings, a constraint map showing where losses arise in the system, an economic assessment of the value impact of identified gaps and a prioritised action plan with concrete implementation steps.
- What You Receive
Title | Description |
|---|---|
Visual Documentation | Photographic and schematic records of critical equipment condition, feed system configuration and identified defects |
Baseline Dataset | Measured performance data for future monitoring, trend tracking, and process optimisation |
Action Plan | Prioritised recommendations with defined implementation path, effort estimate, and expected performance impact |
Economic Assessment | Quantification of operating cost and value losses attributable to identified performance gaps |
Performance Benchmarking | Comparison of current ore sorting performance against design values, commissioning results and industry peers |
Constraint Map | Visual identification of mechanical, sensor, process and operational bottlenecks in the ore sorting system |
OEE Breakdown | Availability, performance, and quality components with root-cause analysis of losses for each |
Audit Report | Structured summary of findings, performance metrics, and improvement potential across all assessed areas |
- Why a Measured Baseline Matters
When an ore sorting machine underperforms, the cause is rarely self-evident. Recovery loss can originate in the sensor, the feed, the ejection system or upstream in the circuit - and these sources are easily confused with one another. Diagnosing the wrong one is expensive: it can lead to unnecessary capital spend on equipment that was never the limiting factor or to writing off a feed source that a correctly configured machine could process profitably.
What protects an operation from that outcome is a diagnosis built on physical measurement and benchmarked against the intrinsic potential of the ore actually being processed. ROKKSTA's audits separate material-driven limitations from machine-driven limitations and sensor-driven losses from mechanical ejection losses, using measured data rather than assumptions. When sensor calibration is the problem, we show it quantitatively. When threshold settings are misaligned with the current ore, we demonstrate it. When feed preparation is the limiting factor rather than the machine, we identify that too - protecting the operation from unnecessary equipment expenditure.
A quantified baseline is particularly valuable in three situations: when underperformance is being attributed to the ore without evidence, when the operation is considering a capital investment in additional ore sorting capacity and when a long-term supply or service contract is being negotiated. A measured baseline is the most defensible foundation for each of these conversations.
- Benefits to Your Operation
Recover hidden value - identify and correct the ore sorting performance losses that accumulate silently without triggering production alarms
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Protect recovery - reduce Type 2 errors (ore to tailings) that are directly eroding mineral recovery and revenue
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Reduce dilution - address Type 1 errors (waste to concentrate) that are increasing downstream processing costs and reducing product grade
Extend equipment life - identify mechanical wear, nozzle degradation, and calibration drift before they cause component failure or unplanned downtime
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Quantify return on investment - establish a measured performance baseline that demonstrates the economic value of your ore sorting installation to management and investors
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Prepare for operational changes - understand your ore sorting system's current state before changing the ore blend, modifying the upstream circuit, or expanding capacity
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Build a defensible performance record - maintain documentation for use in contract negotiations, insurance assessments, and investment decisions
- Part of a Structured Ore Sorting Workflow
Equipment audits connect to the full ROKKSTA ore sorting workflow in both directions:
← Sortability Testing provides the intrinsic sortability baseline and sensor amenability data that are used in the audit as reference benchmarks. Where this baseline does not exist for the current ore type, ROKKSTA can conduct targeted amenability testing as part of the audit scope, establishing whether observed underperformance is attributable to the machine or to a material change.
← Calibration Standards - for XRT and other sensor-based ore sorting systems, calibration standards that accurately represent the ore's physical and compositional properties are essential for maintaining sensor performance between audits. ROKKSTA develops bespoke calibration standards as a standalone service and their specification is often informed by audit findings.
→ Ore Characterisation - where an audit reveals that feed material properties have changed significantly since installation, a targeted ore characterisation programme may be needed to re-establish the intrinsic sortability baseline and re-optimise sensor thresholds for the current ore.
→ Process Development - where audit findings identify structural limitations in the ore sorting circuit design - feed preparation, screening or circuit configuration - ROKKSTA's process development service can evaluate redesign options and model their performance and economic impact.
Frequently Asked Questions
- Get in Touch With ROKKSTA
With objective analysis, actional recommendations and training, ROKKSTA ensures your sorting equipment delivers consistent results where it matters most - on the bottom line.
