By Anthony Hamilton, Mechanical Engineer and Industry Analyst
Australia’s relationship with China has always been a balancing act between economic dependence and strategic independence. Nowhere is that tension clearer than in our trade of iron ore — the mineral that built both our national budget and China’s skyline.
Imagine, then, a bold decision: Australia deliberately cuts its iron ore exports to China by half and pivots toward domestic manufacturing — especially green steel and renewable-powered industry. What would that mean for our economy, our global influence, and our future as an industrial nation?
The answer is both disruptive and transformative.
The Shock: Short-Term Pain
Let’s be clear: halving iron ore exports would jolt the economy.
Australia exported about 900 million tonnes of iron ore in 2024–25, worth roughly A$160 billion, with China buying four-fifths of it. Slashing that volume by half would pull A$80–90 billion out of export revenue almost overnight. Even if prices spiked 50% amid global shortages, our GDP would still take a hit of 2–3% in the first years — a deliberate, self-imposed economic slowdown.
Western Australia, which lives and breathes the ore trade, would feel it most: reduced royalties, idle capacity, and strained state budgets. Canberra’s tax intake could drop by A$10–15 billion per year in the early phase.
But these are short-term tremors — not structural decline. The question is whether we can replace raw-ore exports with something better: value-added industrial activity on Australian soil.
The Transition: Turning Rocks into Revenue
If half of that diverted ore were converted into green steel, the economic story changes dramatically. One tonne of steel is worth four to six times more than the same tonne of ore. Even modest domestic processing could create an A$100 billion green industry within a decade — generating thousands of high-skill jobs across hydrogen, renewables, materials science, and engineering.
Projects in Whyalla, Gladstone, and the Pilbara already point the way. With the right investment — perhaps A$60–100 billion over ten years — Australia could build the capacity to supply its own construction, defence, and transport sectors while exporting carbon-neutral steel to the world.
That’s not deglobalisation. It’s smart industrialisation — keeping the value chain at home instead of shipping our competitive advantage overseas.
The Payoff: Long-Term Strength
By 2035, the payoff could be substantial:
GDP grows larger and more balanced, driven by advanced manufacturing.
Australia becomes a reliable producer of green steel, battery materials, and hydrogen infrastructure.
Dependence on Chinese demand declines, while new trade with India, Japan, Korea, and Europe expands.
In this scenario, Australia’s GDP could be 2–4% higher than the business-as-usual case — smaller mining exports, but far greater industrial depth. It’s a shift from volume to value, from being the world’s quarry to being part of its workshop again.
The Risk: A Test of Political Will
Such a move isn’t without risk. China would almost certainly retaliate — delaying other imports, applying political pressure, and exploiting our internal divisions. The mining lobby would fight hard to protect its margins. Politicians would face the same question every reformer does: why risk the comfortable present for an uncertain future?
Yet the uncomfortable truth is that comfort has bred complacency. Australia’s prosperity is overly reliant on shipping low-value resources to one buyer. That’s not economic freedom — its dependency dressed as success.
The Opportunity: Building the Next Holden Moment
Half a century ago, Holden symbolised a confident, self-sufficient industrial Australia. Its closure marked the end of that era. A green-steel renaissance could be the new Holden moment — a chance to reconnect engineering, manufacturing, and national purpose. It would anchor new jobs, restore industrial pride, and ensure that Australia competes not on cost, but on competence.
We’d still dig things up — but we’d also make things again.
Conclusion: A Strategic Rebalance, Not an Economic Gamble
Cutting 50% of iron ore exports to China would be a strategic recalibration, not an act of economic self-harm. It would cost us in the short run, but it could redefine us in the long run — from a resource economy to a resilient, innovation-driven nation.
For decades, Australia’s industrial conversation has ended with one refrain: “We can’t afford to make things anymore.” Perhaps the truth is the opposite.
A Systems Engineering Approach for Reliable Coal Handling
In coal mining operations, transfer chutes play a deceptively small role with disproportionately large impacts. They sit quietly between conveyors, crushers, and stockpiles, directing tonnes of coal every hour. Yet when a chute is poorly designed or not maintained, the whole coal handling system suffers: blockages stop production, dust creates safety and environmental hazards, and worn liners demand costly maintenance shutdowns.
At Hamilton by Design, we believe coal chute design should be treated not as a piece of steelwork, but as a systems engineering challenge. By applying systems thinking, we connect stakeholder requirements, material behaviour, environmental factors, and lifecycle performance into a holistic design approach that delivers long-term value for mining operations in the Hunter Valley and beyond.
Coal Chutes in the Mining Value Chain
Coal chutes form the links in a chain of bulk material handling equipment:
ROM bins and crushers feed coal into the system.
Conveyors carry coal across site, often over long distances.
Transfer chutes guide coal between conveyors or onto stockpiles.
Load-out stations deliver coal to trains or ports for export.
Although they are small compared to conveyors or crushers, coal chutes are often where problems first appear. A well-designed chute keeps coal flowing consistently; a poorly designed one causes buildup, spillage, dust emissions, and accelerated wear. That’s why leading operators now see chute design as a critical system integration problem rather than just a fabrication task.
Systems Engineering in Coal Chute Design
Systems engineering is the discipline of managing complexity in engineering projects. It recognises that every component is part of a bigger system, with interdependencies and trade-offs. Applying this mindset to coal chute design ensures that each chute is considered not in isolation, but as part of the broader coal handling plant.
1. Requirements Analysis
The first step is gathering and analysing stakeholder and system requirements:
Throughput capacity: e.g. handling 4,000 tonnes per hour of coal.
Material properties: coal size distribution, moisture content, abrasiveness, stickiness.
Safety requirements: compliance with AS/NZS 4024 conveyor safety standards, confined space entry protocols, guarding, and interlocks.
Environmental compliance: dust, noise, and spillage limits.
Maintenance objectives: target liner life (e.g. 6 months), maximum downtime per liner change (e.g. 30 minutes with two workers).
A structured requirements phase reduces the risk of costly redesign later in the project.
2. System Design and Integration
Once requirements are defined, the design process considers how the chute integrates into the coal handling system:
Flow optimisation using DEM: Discrete Element Modelling allows engineers to simulate coal particle behaviour, test different geometries, and reduce blockages before steel is ever cut.
Dust control strategies: designing chutes with enclosures, sprays, and extraction ports to minimise airborne dust.
Wear management: predicting wear zones, selecting suitable liner materials (ceramic, Bisplate, rubber composites), and ensuring easy access for replacement.
Structural and safety design: ensuring the chute can withstand dynamic loads, vibration, and impact, while providing safe access platforms and guarding.
Interfaces with conveyors and crushers: alignment, skirt seals, trip circuits, and integration with PLC/SCADA control systems.
By treating the chute as a subsystem with multiple interfaces, designers avoid the “bolt-on” mentality that often leads to operational headaches.
3. Verification and Validation
The systems engineering V-model reminds us that every requirement must be verified and validated:
System validation: commissioning with live coal flow, dust monitoring against limits, maintainability time trials for liner change.
By linking requirements directly to tests in a traceability matrix, operators can be confident that the chute is not only built to spec, but proven in operation.
Lifecycle Engineering: Beyond Installation
Good chute design doesn’t stop at commissioning. A lifecycle engineering mindset ensures the chute continues to deliver performance over years of operation.
Maintainability: modular liners, captive fasteners, hinged access doors, and clear procedures reduce downtime and improve worker safety.
Reliability: DEM-informed designs and wear-resistant materials reduce the frequency of blockages and rebuilds.
Sustainability: dust suppression and enclosure strategies reduce environmental impact and support community and regulatory compliance.
Continuous improvement: feedback loops from operators and maintenance teams feed into the next design iteration, closing the systems engineering cycle.
A Rich Picture of Coal Chute Complexity
Visualising the coal chute system as a rich picture reveals its complexity:
Operators monitoring flow from control rooms.
Maintenance crews working in confined spaces, replacing liners.
Design engineers using DEM simulations to model coal flow.
Fabricators welding heavy plate sections on site.
Environmental officers measuring dust levels near transfer points.
Regulators and community monitoring compliance.
This web of relationships shows why coal chute design benefits from systems thinking. No single stakeholder sees the whole picture—but systems engineering does.
Benefits of a Systems Engineering Approach
When coal chute design is guided by systems engineering principles, operators gain:
Higher reliability: smoother coal flow with fewer blockages.
Lower maintenance costs: liners that last longer and can be swapped quickly.
Improved compliance: dust, spillage, and safety issues designed out, not patched later.
Lifecycle value: less unplanned downtime and a lower total cost of ownership.
In short, systems engineering transforms coal chutes from weak links into strong connectors in the mining value chain.
Case Study: Hunter Valley Context
In the Hunter Valley, coal mines have long struggled with transfer chute problems. Companies like T.W. Woods, Chute Technology, HIC Services, and TUNRA Bulk Solids have all demonstrated the value of combining local fabrication expertise with advanced design tools. Hamilton by Design builds on this ecosystem by applying structured systems engineering methods, ensuring each chute project balances performance, safety, cost, and sustainability.
Conclusion
Coal chute design might seem like a small detail, but in mining, details matter. When transfer chutes fail, production stops. By applying systems engineering principles—from requirements analysis and DEM modelling to verification, lifecycle planning, and continuous improvement—we can design coal chutes that are reliable, maintainable, and compliant.
At Hamilton by Design, we believe in tackling these challenges with a systems mindset, delivering solutions that stand up to the realities of coal mining.
Call to Action
Are you struggling with coal chute blockages, dust, or costly downtime in your coal handling system?
Contact Hamilton by Design today and discover how our systems engineering expertise in coal chute design can optimise your mining operations for performance, safety, and sustainability.
This paper examines the mechanical degradation, failure mechanisms, and system-level reliability implications of Australia’s ageing coal-fired power generation assets, focusing on Callide Power Station (Queensland) and Yallourn Power Station (Victoria). Both stations have experienced significant mechanical failures in the past five years, exposing vulnerabilities in maintenance, asset management, and risk governance under conditions of declining reinvestment. From a mechanical engineering standpoint, these failures illustrate the predictable end-of-life behaviour of large rotating and pressure-bound systems when maintenance expenditure, material renewal, and operational monitoring decline. The paper argues that sustained industrial reliability—and thus national energy and employment security—requires engineering-informed policy that balances decarbonisation with technical integrity management.
Coal-fired power stations are among the most complex mechanical systems ever built in Australia. They integrate high-temperature, high-pressure thermodynamic processes with massive rotating equipment, lubrication systems, and precision alignment tolerances.
From a mechanical engineer’s perspective, their reliability depends on three interlinked pillars:
Structural and material integrity,
Lubrication and vibration control, and
Predictive maintenance and monitoring.
However, as the nation accelerates toward renewable transition targets, investment in these legacy systems has declined. Mechanical failures at Callide and Yallourn are therefore not random accidents but the mechanical manifestation of economic and policy choices.
This analysis seeks to understand those failures in engineering terms, predict future risks, and outline how a re-commitment to industrial infrastructure and jobs requires a concurrent commitment to mechanical reliability.
Technical Overview of Recent Failures
Callide Power Station
Callide’s units span several generations of design and material technology. The C4 explosion (2021) was catastrophic: the failure originated within the turbine hall, leading to structural collapse and large-scale ejection of debris. Subsequent analysis by CS Energy and external investigators identified battery charger replacement errors, inadequate isolation protocols, and loss of process safety discipline as initiators.
From an engineering integrity perspective, the incident represents a compound failure:
Mechanical systems operated under degraded conditions;
Electrical and process-control systems failed to detect early anomalies;
Organisational maintenance controls were insufficient to interrupt escalation.
Later failures — including the C3 boiler pressure event (2025) and cooling tower collapse (2022) — further confirm that structural materials, corrosion protection, and load-carrying assemblies had entered the fatigue–creep interaction phase of their service life.
Yallourn Power Station
At Yallourn, the August 2025 low-pressure turbine dislodgement occurred after decades of vibration monitoring alarms and bearing wear signals. Earlier (2024) shutdowns for “high vibration alarms” indicated growing rotor dynamic instability. When the Unit 2 turbine dislodged, the damage pattern suggested bearing wear, misalignment, or bolt relaxation leading to component displacement.
In mechanical engineering terms, this is a classic late-life failure sequence:
Fatigue crack initiation in critical load-carrying components (rotor or coupling bolts),
Progressive loosening and unbalance,
Dynamic amplification under operating RPM,
Catastrophic structural displacement.
The turbine’s dislodgement was therefore an expected end-of-life event, accelerated by reduced overhaul investment and ageing metallurgical properties.
Comparative Engineering Analysis
Engineering Dimension
Callide
Yallourn
Comparison / Insight
Failure Type
Explosion / Pressure Containment Breach
Turbine Mechanical Dislodgement
Callide shows energy-release failure; Yallourn a structural integrity loss.
Root Mechanical Cause
Overpressure / process safety
Fatigue, unbalance, bearing or bolt failure
Both reflect cumulative degradation.
Indicative Material State
Creep-fatigued pressure shells; corroded supports
Thermal-fatigued steel, worn journals
Metallurgical ageing dominates both.
Maintenance Culture
Process-safety erosion
Reactive, “run-to-retirement”
Organisational degradation common factor.
System Outcome
Explosion and total destruction
Severe mechanical damage, unit outage
Both reduce grid reliability and reveal systemic neglect.
These failures share a unifying pattern recognised in mechanical reliability theory:
Late-life degradation compounded by maintenance deferral and organisational fatigue produces cascading mechanical failure modes that were once preventable.
Predicting Future Failure Behaviour
Mechanical engineers use reliability-centred maintenance (RCM) models to quantify end-of-life risk. For rotating equipment, mean time to failure (MTTF) typically decreases exponentially once fatigue propagation exceeds ~70 % of material endurance life.
Data from the National Electricity Market (NEM) indicates:
Forced outage frequency has doubled since 2012.
Vibration and lubrication alarms are rising in frequency.
Unit unavailability correlates strongly (R² > 0.8) with turbine age and last major overhaul date.
Projected forward, these indicators imply that without major overhauls or component replacements, most Australian coal units will face critical mechanical reliability decline by 2032–2035.
Engineering Economics and Policy Interaction
From an engineering management perspective, the problem is not purely technical — it is thermo-economic.
A major turbine retrofit (~A$25–40 million per unit) is uneconomic for plants scheduled for closure in under a decade.
The probability of catastrophic failure increases sharply as the cost of prevention declines below the cost of repair.
This is the engineering expression of policy-induced obsolescence: political commitments to retire coal reduce the incentive to sustain its mechanical integrity, even while industries still depend on its output.
Industrial Reliability and the Employment Interface
Reliable baseload power is the foundation for industrial continuity. From the standpoint of a mechanical engineer, industrial productivity is a function of mechanical uptime: Productivity=f(Power Reliability,Maintenance Efficiency)\text{Productivity} = f(\text{Power Reliability}, \text{Maintenance Efficiency})Productivity=f(Power Reliability,Maintenance Efficiency)
When power generation becomes intermittent—whether from renewable intermittency or coal unreliability—industrial operations must compensate with redundancy, backup generation, or load-shedding. These add capital and operational costs that ultimately affect employment.
Regional Implications
Queensland retains a stronger firm power horizon (coal + gas + hydro until ~2035), giving industry more operational certainty.
Victoria, by contrast, will face a reliability inflection point after Yallourn (2028) and Loy Yang A (2035) closures.
Without firm generation or large-scale storage online, manufacturing regions risk power volatility—directly translating to production downtime and job insecurity.
Engineering the Transition: Commitment to Jobs and Infrastructure
From a mechanical engineering ethics and systems standpoint, a commitment to industry must be synonymous with a commitment to mechanical reliability. That requires three converging actions:
Asset Integrity Management: Continuous structural health monitoring, vibration analysis, and overhaul planning for remaining thermal units. Even in decline, they must be safely and predictably retired.
Design and Commissioning of Replacement Systems: Engineers must ensure that renewable generation, storage, and transmission assets meet equivalent reliability and maintainability standards. This includes redundancy design, grid inertia replacement, and mechanical resilience of large rotating machinery (e.g., pumped hydro, turbines, bearings).
Workforce Transition as Engineering Continuity: The skills used to maintain turbines, bearings, and boilers are transferable to wind, hydro, and hydrogen equipment. Protecting those jobs preserves both mechanical capability and national energy security.
Engineering Conclusions
From a mechanical engineer’s viewpoint, the failures at Callide and Yallourn are textbook case studies of end-of-life degradation under policy-driven neglect. They illustrate that:
Mechanical degradation is predictable — vibration, lubrication, and thermal-stress indicators were present years before failure.
Organisational and policy decisions override engineering recommendations — maintenance deferral was economic, not technical.
Systemic reliability cannot be sustained without mechanical investment — whether in turbines, batteries, or hydro equipment, engineering integrity remains central.
A national commitment to industry equals a commitment to engineering.
If Australia seeks to safeguard its industrial base and employment, it must invest not only in new energy technologies but in the mechanical soundness of the systems that bridge the transition. Neglecting this will reproduce the same failure patterns—just in new forms of infrastructure.
References (Indicative)
CS Energy (2024). Callide C4 Incident Investigation Summary.
WattClarity (2025). Analysis of Yallourn Unit 2 Trip and Frequency Response.
Robots are no longer the stuff of science fiction—they are embedded in our factories, warehouses, and even food-processing plants. They promise efficiency, speed, and the ability to take on dangerous jobs humans shouldn’t have to do. Yet, as recent headlines show, this promise comes with serious risks. From the lawsuit against Tesla over a robotic arm that allegedly injured a worker to the tragic death of a Wisconsin pizza factory employee crushed by a machine, the conversation about human–robot relations has never been more urgent.
This blog post explores the promise and peril of robotics in the workplace, drawing lessons from recent incidents and asking: how do we ensure humans and robots can coexist safely?
The Rise of Robotics in Everyday Work
Robotics is spreading quickly across industries. Automotive giants like Tesla rely on robotic arms for precision assembly, while food plants use automated systems to handle packaging and processing. According to the International Federation of Robotics, robot installations worldwide continue to grow year after year. For businesses, it’s a clear win: fewer errors, lower costs, and reduced human exposure to dangerous tasks.
But with robots entering smaller facilities—where safety infrastructure may be weaker—the risks grow. A miscalibrated robot, a missed safety step, or a poorly trained operator can turn a productivity tool into a deadly hazard.
When Robots Go Wrong: Lessons from Recent Cases
Tesla’s Robotic Arm Lawsuit A former technician at Tesla claims he was struck and knocked unconscious by a robotic arm while performing maintenance. The lawsuit highlights a crucial point: safety procedures like lockout/tagout aren’t optional—they are lifesaving. When machines are energized during servicing, even a momentary slip can have devastating consequences.
Wisconsin Pizza Factory Fatality In a smaller manufacturing plant, a worker lost his life after being crushed by a robotic machine. Unlike Tesla, this wasn’t a high-tech car factory but a food facility—showing that robotics risks extend far beyond Silicon Valley. Smaller plants may lack robust safety training, yet they are increasingly embracing automation.
Both cases are tragic reminders that technology alone can’t guarantee safety. Human oversight, training, and organizational commitment to safety matter just as much.
The Human Side of Robotics
When people think about robots at work, they often picture job displacement. But for many workers, the immediate concern is safety. Studies show that trust plays a huge role: workers who believe robots are reliable tend to perform better. However, misplaced trust—assuming a machine will always stop when needed—can be just as dangerous as fear or mistrust.
Beyond physical risks, robots can also affect morale and mental health. Workers may feel devalued or expendable when machines take over critical tasks. The challenge isn’t just engineering safer robots—it’s creating workplaces where humans feel respected and protected.
Building a Safer Future Together
So how do we strike the right balance between robotics innovation and human well-being? A few key steps stand out:
Design Safety Into the Machine: Emergency stops, advanced sensors, and fail-safes should be standard features—not optional add-ons.
Enforce Safety Protocols: OSHA’s lockout/tagout rules exist for a reason. Employers must ensure that servicing robots without proper shutdowns is never allowed.
Invest in Training: Robots are only as safe as the people who interact with them. Ongoing, practical training helps prevent accidents.
Foster a Safety Culture: Workers should feel empowered to report unsafe practices without fear of retaliation.
Update Regulations: As robots spread into more industries, regulators must adapt. International safety standards like ISO 10218 need to be more widely enforced, especially in smaller facilities.
Conclusion
Robotics is here to stay. It has the potential to make our workplaces more efficient, less physically demanding, and even safer. But incidents like those at Tesla and the Wisconsin pizza plant remind us that without proper safeguards, the cost of automation can be measured in human lives.
The future of human–robot relations doesn’t have to be one of fear or tragedy. With the right mix of engineering, regulation, and workplace culture, robots and humans can work side by side—not as rivals, but as partners. The question isn’t whether we should embrace robotics, but whether we’ll do so responsibly, putting people’s safety and dignity first.
At Hamilton By Design, we know that 3D scanning has become an essential tool for modern engineering — from capturing as-built conditions on construction sites to modeling complex processing plants and validating manufacturing layouts. But not all scanners are created equal, and selecting the right technology is crucial to getting reliable data and avoiding costly surprises later in the project.
3D Scanning for Construction Sites
For construction and infrastructure projects, coverage and speed are the top priorities. Terrestrial Laser Scanning (TLS) and LiDAR systems like the FARO Focus S70 are ideal for quickly capturing entire job sites with millimetre-level accuracy. These scanners allow engineers and project managers to:
Verify as-built conditions against design models
Detect clashes early in the process
Support accurate quantity take-offs and progress documentation
TLS works well in tough environments — dust, sunlight, and complex geometry — making it a perfect fit for active building sites.
3D Scanning for Manufacturing & Processing Plants
When it comes to manufacturing facilities and mining processing plants, accuracy and detail matter even more. Scans are often used for:
Retrofit planning and clash detection in tight plant rooms
Structural steel and conveyor alignment checks
Equipment layout for expansion projects
Here, combining TLS with feature-based CAD modeling allows us to deliver data that is usable for engineering design, ensuring that new equipment fits exactly as intended.
We’re Here to Help
Hamilton By Design doesn’t sell scanners — we focus on providing unbiased, engineering-driven advice. If you’re unsure which scanning approach is right for your project, we’re happy to share our experience and guide you toward the best solution.
Feel free to get in touch to discuss your project needs — whether it’s a construction site, manufacturing facility, or processing plant, we can help you turn accurate scan data into actionable engineering insights.
In modern mining, where uptime is money and safety is non-negotiable, understanding the geometry of your process plant is critical. Every conveyor, chute, pipe rack, and piece of equipment must fit together seamlessly and operate reliably — but plants are messy, dusty, and constantly changing. Manual measurement with a tape or total station is slow, risky, and often incomplete.
This is where LiDAR scanning (Light Detection and Ranging) has become a game-changer. By capturing millions of precise 3D points per second, LiDAR gives engineers, maintenance planners, and operators an exact digital replica of the plant — without climbing scaffolds or shutting down equipment. In this post, we’ll explore how mining companies are using LiDAR scanning to solve real problems in processing plants, improve safety, and unlock operational efficiency.
What Is LiDAR Scanning?
LiDAR is a remote sensing technology that measures distance by firing pulses of laser light and recording the time it takes for them to return. Modern terrestrial and mobile LiDAR scanners can:
Capture hundreds of thousands to millions of points per second
Reach tens to hundreds of meters, depending on the instrument
Achieve millimeter-to-centimeter accuracy
Work in GPS-denied environments, such as inside mills, tunnels, or enclosed plants (using SLAM — Simultaneous Localization and Mapping)
The output is a point cloud — a dense 3D dataset representing surfaces, equipment, and structures with stunning accuracy. This point cloud can be used as-is for measurements or converted into CAD models and digital twins.
Why Process Plants Are Perfect for LiDAR
Unlike greenfield mine sites, processing plants are some of the most geometry-rich and access-constrained areas on site. They contain:
Complex networks of pipes, conveyors, tanks, and structural steel
Moving equipment such as crushers, mills, and feeders
Dusty, noisy, and hazardous environments with limited safe access
All these factors make traditional surveying difficult — and sometimes dangerous. LiDAR enables “no-touch” measurement from safe vantage points, even during operation. Multiple scans can be stitched together to create a complete model without shutting down the plant.
Applications of LiDAR in Process Plants
1. Wear Measurement and Maintenance Planning
LiDAR has revolutionized how mines measure and predict wear on critical process equipment:
SAG and Ball Mill Liners – Portable laser scanners can capture the exact wear profile of liners. Comparing scans over time reveals wear rates, helping maintenance teams schedule relines with confidence and avoid premature failures.
Crusher Chambers – Scanning inside primary and secondary crushers is now faster and safer than manual inspections. The resulting 3D model allows engineers to assess liner life and optimize chamber profiles.
Chutes and Hoppers – Internal scans show where material buildup occurs, enabling targeted cleaning and redesign to prevent blockages.
Result: Reduced downtime, safer inspections, and better forecasting of maintenance budgets.
2. Retrofit and Expansion Projects
When modifying a plant — installing a new pump, rerouting a pipe, or adding an entire circuit — having an accurate “as-built” model is crucial.
As-Built Capture – LiDAR provides an exact snapshot of the existing plant layout, eliminating guesswork.
Clash Detection – Designers can overlay new equipment models onto the point cloud to detect interferences before anything is fabricated.
Shutdown Optimization – With accurate geometry, crews know exactly what to cut, weld, and install — reducing surprise field modifications and shortening shutdown durations.
3. Inventory and Material Flow Monitoring
LiDAR is not just for geometry — it’s also a powerful tool for tracking material:
Stockpile Volumetrics – Mounted scanners on stackers or at fixed points can monitor ore, concentrate, and product stockpiles in real time.
Conveyor Load Measurement – Stationary LiDAR above belts calculates volumetric flow, giving a direct measure of throughput without contact.
Blending Control – Accurate inventory data improves blending plans, ensuring consistent plant feed quality.
4. Safety and Risk Management
Perhaps the most valuable application of LiDAR is keeping people out of harm’s way:
Hazardous Floor Areas – When flooring or gratings fail, robots or drones with LiDAR payloads can enter the area and collect data remotely.
Fall-of-Ground Risk – High walls, bin drawpoints, and ore passes can be scanned for unstable rock or buildup.
Escape Route Validation – Scans verify clearances for egress ladders, walkways, and platforms.
Every scan effectively becomes a permanent digital record — a baseline for monitoring ongoing structural integrity.
5. Digital Twins and Advanced Analytics
A plant-wide LiDAR scan is the foundation of a digital twin — a living, data-rich 3D model connected to operational data:
Combine scans with SCADA, IoT, and maintenance systems
Visualize live process variables in context (flow rates, temperatures, vibrations)
Run “what-if” simulations for debottlenecking or energy optimization
As AI and simulation tools mature, the combination of geometric fidelity and operational data opens new possibilities for predictive maintenance and autonomous plant operations.
Emerging Opportunities
Looking forward, there are several promising areas for LiDAR in mining process plants:
Autonomous Scan Missions – Using quadruped robots (like Spot) or SLAM-enabled drones to perform routine scanning in high-risk zones.
Real-Time Change Detection – Continuous scanning of critical assets with alerts when deformation exceeds thresholds.
AI-Driven Point Cloud Analysis – Automatic object recognition (valves, flanges, motors) to speed up model creation and condition reporting.
Integrated Planning Dashboards – Combining LiDAR scans, work orders, and shutdown schedules in a single interactive 3D environment.
Best Practices for Implementing LiDAR
To maximize the value of LiDAR scanning, consider:
Define the Objective – Are you measuring wear, planning a retrofit, or building a digital twin? This affects scanner choice and resolution.
Plan Scan Positions – Minimize occlusions and shadow zones by preplanning vantage points.
Use Proper Registration – Tie scans to a control network for consistent alignment between surveys.
Mind the Environment – Dust, fog, and vibration can degrade data; choose scanners with appropriate filters or protective housings.
Invest in Processing Tools – The raw point cloud is only the start — software for meshing, modeling, and analysis is where value is extracted.
Train Your Team – Build internal capability for scanning, processing, and interpreting the results to avoid vendor bottlenecks.
LiDAR scanning is no longer a niche technology — it is rapidly becoming a standard tool for mining process plants that want to operate safely, efficiently, and with fewer surprises. From mill liners to stockpiles, from shutdown planning to digital twins, LiDAR provides a clear, measurable view of assets that was impossible a decade ago.
For operations teams under pressure to deliver more with less, the case is compelling: better data leads to better decisions. And in a high-stakes environment like mineral processing, better decisions translate directly to improved uptime, reduced costs, and safer workplaces.
The next time you’re planning a shutdown, a retrofit, or even just trying to understand why a chute is plugging, consider pointing a LiDAR scanner at the problem. You may be surprised at how much more you can see — and how much time and money you can save.
