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      <title>GEOVIA</title>
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      <description>GEOVIA</description>
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      <![CDATA[ Bridging the Gap Between Strategic Plans and Operational Mine Schedules ]]>
      </title>
      <link>https://blog.3ds.com/brands/geovia/bridging-the-gap-between-strategic-plans-and-operational-mine-schedules/</link>
      <guid>https://blog.3ds.com/guid/303011</guid>
      <pubDate>Mon, 01 Jun 2026 09:50:08 GMT</pubDate>
      <description>
      <![CDATA[ How GEOVIA MineSched enables mine planners to generate safe, auditable, and executable short and medium-term  schedules without scripting complexity or unnecessary data reconciliation overhead.
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      <![CDATA[ 
In mine planning, the transition from strategic objectives to operational execution represents one of the most demanding challenges for planning teams. Long-term optimization tools, designed to maximize NPV, define optimal pit shells, and model life-of-mine scenarios, operate over multi-year horizons and rely on algorithms such as Lerchs-Grossmann, Pseudoflow or DBS. But these tools are not built to address the operational realities that govern day-to-day production: equipment constraints, active bench management, haulage route efficiency, or grade blending requirements at the plant.



GEOVIA MineSched, Dassault Systèmes&#8217; short- and medium-term mine planning and scheduling software, is designed to close this gap. Operating at the tactical planning layer across months, weeks, and days, MineSched transforms validated strategic plans into practical, executable operational schedules within a single, integrated environment.




Important distinction: MineSched does not perform optimization. It focuses on scheduling, applying heuristic algorithms to achieve user-defined targets within configured constraints. The mine planner configures the planning scenario and remains responsible for validating the resulting outputs. MineSched operates within existing mine designs and does not generate them.








From Strategic Optimization to Tactical Execution



Strategic planning tools address long-term objectives such as NPV maximization, pit shell definition, and life-of-mine scheduling. MineSched operates at the next layer, translating those outputs into schedules that reflect operational realities including equipment availability, destination constraints, production targets, and spatial precedence. 




The integration between these two layers is critical. A strategic plan that cannot be executed reliably at the tactical level introduces reconciliation risk. MineSched addresses this challenge by using the block model as its single source of truth, ensuring consistency across all planning stages while eliminating the need to re-import or reconcile data across disconnected systems. 




The practical outcome is that a mine planner can configure a reliable base scenario in under one hour, with full auditability at every step, without relying on custom scripting or external specialist services.



Core Planning Capabilities



Pit Sequencing with Operational Safety Controls



Tactical pit sequencing in MineSched generates extraction sequences that comply with defined operational safety parameters while reflecting real mining conditions.



It allows planners to control key constraints such as the maximum number of active benches per period, ensuring safe levels of simultaneous bench exposure. Minimum mining widths are enforced to guarantee equipment access and face stability. Mining direction flexibility also supports rapid scenario comparison when ground conditions or priorities change.




Sequencing can be reviewed through configurable animations and dynamic dashboards, providing both visual and analytical confirmation that the sequence is safe and operational before field execution.








Target-Based Sequencing for Grade and Ratio Control



Short-term planning requires balancing plant feed consistency, stripping ratio, and ore blending. MineSched addresses this through its Quality Targets and Ratios module, enabling planners to define operational targets directly within the schedule.



These include blend targets to maintain consistent head grade and maximize plant recovery, a constant stripping ratio to ensure operational continuity, and material proportion targets to control the throughput of high-grade ore.



Because these targets are directly linked to the scheduling engine, the impact of sequencing decisions on plant feed can be evaluated immediately, reducing the risk of grade shortfalls and limiting unexpected processing variability.



Haulage Planning and Fleet Modeling



Short-term schedule reliability depends heavily on accurate haulage assumptions. MineSched integrates haulage planning directly into the scheduling environment.




It enables automatic route definition, generating optimal haul paths based on mine geometry and destination configurations. Explicit road and access modeling allows haul roads and bench access roads to be defined so the plan reflects actual site infrastructure.




Fleet aging simulation adjusts equipment utilization over time to reflect realistic productivity changes, while seasonal weather integration accounts for adverse conditions that impact haulage performance, reducing gaps between scheduled and actual results.



Production Priorities: Sequencing All Mining Activities



Operational schedules must extend beyond material extraction. The Production Priorities workflow in MineSched extends sequencing control to all mining activities, including drilling, blasting, loading, and hauling.



Precedence rules are automatically generated based on bench elevation, reducing manual configuration effort. Additional priority rules can be defined to minimize bottlenecks between activities.



This workflow ensures continuity between short-term and long-term planning horizons, using spatial precedence parameters that maintain consistency as the planning window evolves.



Stockpile and Tailings Dam Management



Material flow management is a key part of operational planning, supported directly within MineSched.



Stockpile capacity rules define maximum constraints for all stockpiles, with overflow management ensuring practical routing under varying production conditions. Integrated tailings modeling covers tonnages, dynamic capacities, and pulp generation, including fixed or variable recovery factors by material, grade, and commodity.



The system also supports flexible grade and metal unit configuration (g/t, oz/t, and others), aligning outputs with plant and corporate reporting requirements. Integrated reporting enables dashboards and extended reports to be generated directly in the tool, removing the need for external data processing before validation and communication.



Why this matters to your team?



The cumulative value of MineSched lies not only in its individual capabilities, but in the overall planning workflow it enables. By consolidating geology, mine design, equipment constraints, material destinations, and production targets within a single environment, MineSched reduces the data fragmentation and manual reconciliation that typically consume planning resources at the tactical level.




Auditability at every configuration step ensures that scheduling decisions can be reviewed, justified, and communicated across planning and operations teams, which is critical for maintaining confidence in the plan as conditions evolve. Rapid scenario generation and visual validation capabilities also allow planners to respond to operational changes without rebuilding the schedule from the ground up.




The result is a planning process that is faster to execute, more transparent in its assumptions, and more closely aligned with the operational realities that determine whether a schedule can be successfully achieved.











FURTHER READING



For a comprehensive guide to efficient mine scheduling workflows, scenario configuration best practices, and productivity benchmarks with GEOVIA MineSched, download the eBook:



Efficient Mine Scheduling: Maximize Productivity with GEOVIA MineSched







Community is a place for GEOVIA users – from beginners to experts and everyone in between – to get answers to your questions, learn from each other, and network.&nbsp;Join our community to know more:



GEOVIA User Community&nbsp;–&nbsp;Read about industry topics from GEOVIA experts, be the first to know about new product releases and product tips and tricks, and share information and questions with your peers. All&nbsp;industry professionals are welcome to learn, engage, discover and share knowledge to shape a sustainable future of mining. &nbsp;



New member?&nbsp;Create an account, it’s free!&nbsp;Learn more about this community&nbsp;HERE.
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      <title>
      <![CDATA[ The Hidden Breakdown in Short-Term Mine Scheduling ]]>
      </title>
      <link>https://blog.3ds.com/brands/geovia/the-hidden-breakdown-in-short-term-mine-scheduling/</link>
      <guid>https://blog.3ds.com/guid/302785</guid>
      <pubDate>Wed, 27 May 2026 09:52:19 GMT</pubDate>
      <description>
      <![CDATA[ The key question for most operations is therefore not whether more capable scheduling workflows exist, but whether the current toolset is being fully leveraged in practice.
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      <![CDATA[ 
The daily reality of a tactical scheduler



You build the shift plan. The survey data comes in late. A loader breaks down on the eastern ramp. Grade control flags a dilution issue at the face you just committed to. By 9 AM, the schedule you spent two hours constructing the night before is already partially obsolete.




This is not a niche problem. It is the everyday experience of short-term and tactical mine planning engineers across open-pit and underground operations worldwide. And yet, for all the progress the industry has made in reserve estimation, long-term strategic planning, and fleet management automation, the short-term scheduling layer remains stubbornly fragile in most operations.








The reasons are worth examining carefully — because they have less to do with the skill of the planners and everything to do with structural mismatches in how data, tools, and workflows are organized.



The structural problem: data latency versus planning frequency



Short-term scheduling operates on a cadence that is not aligned with the way mine data is typically captured and made available. Blast movement surveys, grade control samples, equipment availability reports, and stockpile inventories each follow different update cycles, whether daily, shift-based, or weekly. In contrast, tactical planners are expected to produce constraint-aware, actionable schedules at a much higher frequency.



This creates a persistent information gap. Planning decisions around sequencing and equipment allocation are often made using data that is already outdated by several hours, and in some cases, several days. The operational consequence is a continuous chain of reactive adjustments, including reblasting, equipment re-routing, emergency drawdowns from stockpiles, and last-minute revisions to mill feed targets.



Importantly, these adjustments are rarely fully reflected in the formal scheduling system. They are instead managed through informal channels such as emails, radio communications, and individual supervisory experience. Over time, this leads to a progressive divergence between the documented schedule and actual field execution, until the next weekly replanning cycle attempts to re-establish alignment, without necessarily fully resolving the accumulated deviations.



The parallel tool problem



A second structural issue compounds the first: the widespread use of shadow tools. In the absence of scheduling systems that can be updated and iterated quickly enough to keep pace with operational dynamics, planners rely on workarounds such as spreadsheets, whiteboards, custom macros, and informal handovers between shifts.



These tools are not adopted out of preference, but out of necessity. The effort required to update formal systems during an ongoing shift is often too high relative to the operational urgency. This leads to a dual-layer operating model: a formal schedule that remains authoritative in principle but quickly becomes outdated in practice, and an informal layer of real-time adjustments that reflects actual operations but is neither systematically recorded nor integrated into downstream planning processes.




Over time, this informal layer becomes a repository for a large share of tacit operational knowledge. However, because it is not captured in structured systems, it is also highly fragile, and is frequently lost when experienced personnel leave or rotate across sites.








The scenario problem: one plan is never enough



Experienced tactical schedulers understand that committing to a single schedule is, in practice, a simplification rather than a reflection of operational reality. Each plan functions more as a primary scenario accompanied by implicit contingencies. Where should the loader be redeployed if the primary mining face reports higher-than-expected grades? If the crusher line is unavailable for several hours, which stockpile should absorb the shortfall? If weather conditions constrain operations, which blast sequence should be deferred without destabilizing downstream production?



In many operations, these contingency pathways exist only in an informal form. They are rarely modelled explicitly, systematically documented, or evaluated against production objectives and equipment constraints. As a result, when contingencies materialize, the response is often constructed in real time rather than pre-defined. At scale, this reliance on improvisation introduces both inefficiency and cost.




The capacity to rapidly generate, assess, and communicate multiple scheduling scenarios therefore represents a critical capability for tactical planning teams. It shifts scheduling away from a static deliverable and toward a structured decision-support process, where alternatives are explicitly compared rather than implicitly assumed.








So what does solving this actually look like?



The structural issues described above, including data latency, reliance on shadow tools, and single-scenario planning, are addressable. Not through increased effort or additional headcount, but through changes in the tools and workflows that connect raw mine data to executable schedules.




Scheduling platforms designed for tactical use, such as GEOVIA MineSched by Dassault Systèmes, are intended to reduce these gaps by enabling rapid scenario generation, integrating directly with grade control and survey inputs, and allowing planners to iterate on schedules within the same environment used for documentation and communication.








The key question for most operations is therefore not whether more capable scheduling workflows exist, but whether the current toolset is being fully leveraged in practice.







Community is a place for GEOVIA users – from beginners to experts and everyone in between – to get answers to your questions, learn from each other, and network.&nbsp;Join our community to know more:



GEOVIA User Community&nbsp;–&nbsp;Read about industry topics from GEOVIA experts, be the first to know about new product releases and product tips and tricks, and share information and questions with your peers. All&nbsp;industry professionals are welcome to learn, engage, discover and share knowledge to shape a sustainable future of mining. &nbsp;



New member?&nbsp;Create an account, it’s free!&nbsp;Learn more about this community&nbsp;HERE.




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      <title>
      <![CDATA[ Using Emissions Reporting for Higher Transparency and Lower Complexity ]]>
      </title>
      <link>https://blog.3ds.com/brands/geovia/emissions-reporting-for-higher-transparency/</link>
      <guid>https://blog.3ds.com/guid/293233</guid>
      <pubDate>Tue, 07 Oct 2025 12:00:00 GMT</pubDate>
      <description>
      <![CDATA[  ]]>
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      <![CDATA[ 
Adam North, Senior Client Executive Dassault Systèmes &amp; Rohit Prabhu Industry Process Expert, Senior Specialist, Dassault Systèmes



How can environmental reporting become a driver of clarity rather than a burden? For decades, greenhouse gas (GHG) emissions reporting in mining has been seen as a compliance task to endure. Regulatory frameworks, government mandates, and investor scrutiny force companies to monitor and disclose emissions, yet the process often feels like a drain on resources. Spreadsheets, fragmented systems, and manual data entry have turned reporting into a minefield of complexity and risk.



That perception is shifting. With regulators raising the bar and sustainability becoming central to competitiveness, emissions reporting is no longer just about meeting rules, it is about creating value. Mining companies are finding that a clear reporting strategy can simplify compliance, increase transparency, and unlock operational and financial benefits.




Dassault Systèmes’ Mine Operations Management (MOM) solution shows how automation, integration, and emission reconciliation can turn reporting from a headache into a strategic asset.




The Challenge: Complexity in a High-Stakes Landscape



The regulatory environment around mining emissions is rigorous and fragmented. Global frameworks such as the United Nations Sustainable Development Goals (SDGs) set the agenda, while national legislation like Australia’s Corporations Act amendments (2001) and the National Greenhouse and Energy Reporting (NGER) Act (2007) enforce strict reporting. Global Reporting Initiative (GRI) standards — particularly GRI 14 for mining, GRI 302 for energy use, and GRI 305 for emissions — require highly detailed disclosures.







For executives, the challenge is less about intent than execution. Reporting requirements are technical, evolving, and exacting. For example:




Emission factors vary by region, energy source, and equipment type.



Scope 1 (direct) and Scope 2 (indirect) emissions must be calculated differently, depending on whether fuel, electricity, or hybrid systems are used.



Electricity emissions differ by state and grid mix. A mine in Queensland faces different reporting factors than one in Tasmania.




Without the right systems, these variables can overwhelm mining teams, leading to errors, late submissions, and compliance risks.



Why Transparency Matters More Than Ever



Investors want proof that companies are managing climate risks. Regulators demand accurate, auditable disclosures, while communities expect accountability. Transparency is not just about publishing numbers, it’s about showing where those numbers come from. That requires traceability: Every factor, calculation, and equipment specification must be linked to a verifiable source. In traditional systems this is nearly impossible; in a modern, automated system it becomes standard.




Dassault Systèmes’ MOM system, for instance, embeds references from official regulatory spreadsheets directly into the platform. MOM retains references for audit purposes, including emission factors and Global Warming Potential (GWP) values from the regulation.




Reports are not only accurate but defensible, building trust across stakeholders.



Automating Complexity Out of the System







Manual inputs and static spreadsheets are error-prone and struggle under regulatory pressure. Automation changes that.



With MOM, reporting is built into daily operations:




Transactional-level reporting: Every movement of material, every hour of equipment uses, and every kilowatt of power consumed is logged.



Equipment-specific configuration: Trucks, crushers, screeners, and hybrid assets can be modeled with real-world specifications, for example equipment efficiency, fuel or power consumption.



Dynamic emission factors: National and regional constants are imported directly from regulatory spreadsheets, eliminating the need for manual updates.




Automation reduces human error, shortens reporting cycles, and delivers audit-ready disclosures on demand.



Unlocking Operational Insights Through Granularity



The real value of emissions reporting comes not from compliance, but from the insights granular data reveals. For example:




A haul truck climbing a ramp consumes fuel at very different rates than when idling. MOM captures both scenarios, revealing the true energy and emissions cost.



A crusher’s emissions profile changes dramatically depending on whether electricity comes from renewable sources, the grid, or a local mix.



A hybrid screener running on both diesel and electricity can be modeled to reflect actual operating conditions for accurate reporting.





A higher level of visibility helps companies pinpoint &#8220;hotspots&#8221; in real time and act before problems escalate, whether by reassigning workloads, scheduling maintenance, or investing in more efficient assets.




Dashboards and Analytics: Making Data Actionable







Granularity matters only if it is usable. MOM turns complex data into actionable intelligence with dashboards and analytics. Emissions can be visualized by:




Activity such as drilling, hauling, crushing, or reclamation.



Equipment type such as trucks, crushers, or screeners.



Energy sources such as diesel, electricity, or renewables.



Energy consumption purpose such as stationary vs. mobile equipment.









Managers can filter by site, specific equipment, type of energy, emissions scope, timeframe, aligning reporting with both compliance and operational goals. They can also compare year on year performance to see if sustainability initiatives are delivering measurable results.




Reducing Complexity for Small and Mid-Sized Miners



Large mining houses may be able to electrify fleets or invest in renewables, but smaller miners face tighter budgets. For them, streamlined reporting is critical.



Emission reconciliation offers a practical approach:




Target the highest-emission assets instead of attempting fleet-wide upgrades.



Use dashboards to identify where scheduling changes or fuel substitutions have the biggest impact.



Provide transparent, auditable reporting to regulators and investors without major capital outlay.









MOM lowers the barrier to sustainability for smaller miners, keeping them competitive as ESG performance grows more tied to investment.




Building an Integrated Reporting Strategy



A strong emissions reporting strategy cannot sit in isolation; it must be embedded in operational systems. Integrating emission reconciliation into MOM alongside material reconciliation, operational control, and asset performance creates a unified view of operations.



This approach has three key benefits:




Higher transparency: Every number is traceable and auditable.



Lower complexity: Automation removes the need to manually process large spreadsheets or reconcile data across multiple systems.



Actionable insights: Reporting becomes a real-time performance tool, not just an annual compliance task.








Dassault Systèmes&#8217; MOM: Reporting for a Competitive Edge







Mining’s decarbonization journey will take decades, but reporting strategies can deliver value today. Emission reconciliation lets companies meet regulations with confidence, build trust through transparent data, and identify inefficiencies and hotspots. It also lays the groundwork for long-term decarbonization. What was once a burden is becoming a cornerstone of operational excellence.



The industry’s future depends on balancing profitability with responsibility. An emissions reporting strategy built on transparency and simplicity is no longer optional, it is a competitive necessity. By embedding emission reconciliation into operational systems, mining companies can move beyond compliance, reducing complexity while strengthening trust and efficiency. Dassault Systèmes’ Mine Operations Management solution provides the automation, integration, and traceability to make this possible. For companies ready to rethink reporting, it can shift from regulatory checkbox to strategic tool for clarity and long-term competitiveness in a sustainability-driven world.
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      <title>
      <![CDATA[ Cut Mine Planning Time by 70 per cent and Boost Value with Integrated Data, Virtual Twins and Smart Algorithms ]]>
      </title>
      <link>https://blog.3ds.com/brands/geovia/cut-mine-planning-time-by-70-per-cent-and-boost-value-with-integrated-data-virtual-twins-and-smart-algorithms/</link>
      <guid>https://blog.3ds.com/guid/292659</guid>
      <pubDate>Thu, 25 Sep 2025 09:16:16 GMT</pubDate>
      <description>
      <![CDATA[ By modelling not only the physical attributes of a mine but also the interactions between geological, geotechnical, operational and economic factors, virtual twins allow teams to test scenarios before acting in the field. This capability supports both early-stage project evaluation and operational adjustments in response to changing conditions.
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      <![CDATA[ 
Unlocking up to 70 per cent faster mine planning cycles and millions in additional project value is now within reach for operations that combine centralised data systems, virtual twins and advanced optimisation engines.



At the APCOM2025 conference in Perth, Dr Gustavo Pilger, GEOVIA R&amp;D Strategy and Management Director at Dassault Systèmes, presented the keynote The Value Multiplier: Unlocking Potential with Integrated Data and Smart Algorithms. Drawing on more than two decades in mineral resource modelling and geostatistics, Gustavo outlined how combining federated data with next-generation optimisation and design tools can transform the way mines plan, adapt and extract value.



From data overload to strategic insight



Gustavo began by describing a familiar challenge in mining &#8211; the time lost simply locating and consolidating critical information before planning work can begin.



“Think about how much time is spent just gathering the data,” he said. “Where is the latest block model? Is it in the server, or is it the file named ‘final_final’? Who owns it? These delays inflate costs and slow decision-making.”



The problem, he argued, has grown as sensors and digital systems generate ever-increasing volumes of operational and geological data. While valuable, this information often sits in disparate systems, stored in inconsistent formats and managed by teams with varying levels of awareness about data integrity.



The result is inefficiency, risk, and a planning process that remains rigid and linear &#8211; poorly suited to handling the technical, economic and geopolitical changes that routinely disrupt mine schedules.



The case for centralised, standardised and contextualised data



For Gustavo, the starting point for change is treating data as a core business asset. This means adopting centralised systems that not only federate and secure datasets, but also index, sanitise, and contextualise them in space and time.



He explained that using interlinked data models with a shared “language” &#8211; through semantic dictionaries or industry-standard ontologies &#8211; ensures information can be used consistently across processes. This structure also makes the data machine-readable, enabling AI-driven workflows without losing the human context essential for decision-making.



In practical terms, this approach ensures every team member has access to the right version of the right dataset, with permissions and traceability built in. “It’s about putting you in control of your data, rather than letting the data control you,” Gustavo said.



Unlocking the power of virtual twins



Gustavo described how centralised, structured data can be brought to life through virtual twin technology &#8211; digital replicas of assets, systems and processes that simulate behaviour in real time.



By modelling not only the physical attributes of a mine but also the interactions between geological, geotechnical, operational and economic factors, virtual twins allow teams to test scenarios before acting in the field. This capability supports both early-stage project evaluation and operational adjustments in response to changing conditions.



“Virtual twins enable meaningful links between processes and data,” Gustavo said. “It’s this associativity that allows you to keep chasing value, adjusting to uncertainty and unplanned events.”



Beyond generic AI to industry-specific intelligence



While generative AI and large language models (LLMs) have dominated recent headlines, Gustavo emphasised the need for domain-specific approaches in mining. Dassault Systèmes, he said, focuses on building industry LLMs that integrate decades of sector knowledge with ontologies and physics-based models.



“In this context, industrial AI is secure, sovereign and traceable,” he explained. “It doesn’t generate approximations &#8211; it produces reliable, context-aware representations of real-world objects and processes, including their interactions.”



By keeping humans at the centre of the process, these tools aim to amplify collective intelligence, increase decision-making speed, and maintain governance and auditability.



Optimising mine planning with GMX



Gustavo highlighted one of Dassault Systèmes’ latest developments &#8211; the GEOVIA Mine Maximizer (GMX) engine &#8211; as an example of how advanced algorithms can deliver step-change improvements in strategic mine planning.



An evolution of the well-known Bienstock-Zuckerberg algorithm, GMX can achieve near-optimal global scheduling outcomes in far fewer iterations. In trials across 20 projects, it delivered run-times up to 22 times faster than the original method, with results within one per cent of theoretical optimum. In one case study, this translated into an additional US$127 million in net present value.



The performance gains come from combining GMX with a new algorithm for practical phase optimisation, producing mine phases that align closely with actual designs and minimising deviation &#8211; and therefore potential value loss &#8211; between plan and reality.



Generative design for rapid iteration



Integrating optimisation with generative design tools, Gustavo said, creates the ability to automatically adjust mine designs in response to changing parameters without reworking the entire model manually.



He used the example of designing pit ramps for battery or trolley-assist haul fleets. Designers can define entry and exit points, ramp dimensions, slopes, and other operational constraints, then evaluate trade-offs automatically. When parameters change &#8211; due to new geotechnical data, for example &#8211; the design updates instantly, remaining compliant with safety and operational rules.



“This takes away the need to manually edit the design every time,” Gustavo noted. “It means plans can be updated days or even weeks faster than current practice allows.”



Scaling optionality and scenario testing



The combination of federated data, virtual twins, optimisation engines and generative design opens the door to scenario testing at a scale previously impractical.



In one example, an engineering team used the approach to create 23 pit options, analyse multiple mining directions, generate more than 1500 pushback options, and then develop over 9000 possible mining sequences. This allowed them to select a plan robust enough to meet targets across NPV, logistics and ESG metrics, while withstanding uncertainties and potential disruptions.



Such capability, Gustavo argued, fundamentally changes the agility of mine planning. “You can explore many more design alternatives in less time, with less friction, and without risking data integrity,” he said.



Quantifying the gains



Gustavo shared modelling results comparing the conventional, linear approach to mine planning with a flexible, iterative, collaborative process supported by centralised data and smart algorithms.



Across three iterations &#8211; from initial optimisation and design through to changes in geomechanical parameters and design constraints &#8211; engineering hours fell by around 70 per cent. In absolute terms, this meant reducing a typical 71-hour workload to 18.5 hours.



“These savings are mainly due to less rework,” he explained. “When processes are parametrically defined and digitally interconnected, changes propagate automatically through the chain.”



Beyond labour savings, the integrated approach improves review cycles, increases the reliability of plans, and enables faster responses to improved resource definition, engineering decisions, and market shifts.



Enabling capital project transformation



For capital project evaluation, Gustavo positioned the approach as a potential game-changer. By solving complex optimisation problems in minutes rather than days, automatically updating designs, and running thousands of scenario combinations, planners can select plans that meet targets for geotechnical integrity, ESG compliance and financial performance &#8211; all while maximising NPV.



The key, he concluded, is not just the individual technologies but the way they are combined. “The value comes from connecting processes and data, ensuring associativity between them, and enabling robust, fast scenario evaluation,” he said.



Change management remains the biggest barrier



While the enabling technology is already available, Gustavo cautioned that the main obstacles to adoption are organisational, not technical.



“The technology is there,” he said. “The barriers are really processes and people &#8211; change management. Start small, identify the bottlenecks in your operation, and show value. Once management sees the benefit, it opens the path for more experimentation and adoption.”



Human expertise still central



Asked whether engineers risk being replaced as AI becomes more capable, Gustavo was clear: “AI will help us make decisions, but humans will still need to build models, validate data, and decide on the right course of action. The type of work will change, but there will always be a role for skilled people.”



Source: The Rock Wrangler, Sept 2025







Community is a place for GEOVIA users – from beginners to experts and everyone in between – to get answers to your questions, learn from each other, and network.&nbsp;Join our community to know more:



GEOVIA User Community&nbsp;–&nbsp;Read about industry topics from GEOVIA experts, be the first to know about new product releases and product tips and tricks, and share information and questions with your peers. All&nbsp;industry professionals are welcome to learn, engage, discover and share knowledge to shape a sustainable future of mining. &nbsp;



New member?&nbsp;Create an account, it’s free!&nbsp;Learn more about this community&nbsp;HERE.
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      <![CDATA[ Transforming Mine Planning with Parametric Modelling ]]>
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      <link>https://blog.3ds.com/brands/geovia/transforming-mine-planning-with-parametric-modelling/</link>
      <guid>https://blog.3ds.com/guid/292570</guid>
      <pubDate>Wed, 24 Sep 2025 11:16:55 GMT</pubDate>
      <description>
      <![CDATA[ By leveraging aerospace-grade engineering principles, the software allows for dynamic, interconnected design elements that automatically update when changes are made to any part of the mine plan.
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      <![CDATA[ 
What is GEOVIA Underground Designer?



GEOVIA Underground Designer is a specialized software solution that transforms traditional underground mine planning through parametric modeling technology. This innovative tool enables mining engineers to create, evaluate, and modify underground mine designs with unprecedented speed and flexibility. By leveraging aerospace-grade engineering principles, the software allows for dynamic, interconnected design elements that automatically update when changes are made to any part of the mine plan.



According to Christina Ludwicki, GEOVIA industry process expert at Dassault Systèmes, &#8220;Everything is connected. If I change the length of a heading or the position of a point, all the related infrastructure – stopes, drives, raises – update in real time.&#8221; This interconnected approach represents a fundamental shift in how mining engineers conceptualize and develop underground mining innovations.



The software was officially released in July 2025, bringing proven aerospace design methodology to the mining sector through Dassault Systèmes&#8217; technology ecosystem.



Key Capabilities and Features




Parametric modeling framework that connects all design elements mathematically



Real-time updates across the entire mine design when changes are made to any component



Visual scripting engine for customized automation workflows that streamline repetitive tasks



Cloud-based collaboration through the 3DEXPERIENCE platform enabling global team access



Compatibility with various mining methods including longhole stoping, block caving, cut-and-fill, room and pillar, and sublevel caving




The platform integrates CATIA technology, the same engineering software used to design complex aerospace projects like Boeing&#8217;s 777 and 787 aircraft, applying this sophisticated modeling capability to the unique challenges of underground mining environments.



How Does Parametric Design Transform Underground Mining?



Traditional underground mine design has historically been a time-intensive process requiring manual updates across disconnected workflows. When changes occur—whether from new geological data, production targets, or geotechnical constraints—engineers often need to rebuild significant portions of their designs from scratch.



Ludwicki highlighted this industry-wide challenge, noting, &#8220;I come from underground mining and have spent months on a single design, only for it to be changed and thrown away.&#8221; This experience reflects the frustration felt by many mining engineers working with conventional design tools.



The Evolution from Static to Dynamic Mine Planning



GEOVIA Underground Designer transforms this approach by implementing a parametric framework where:




Design elements maintain mathematical relationships with one another, creating a network of interconnected components



Changes to one component automatically propagate throughout the entire model, eliminating redundant work



Engineers can focus on strategic decisions rather than repetitive drafting tasks, improving productivity



Multiple design scenarios can be evaluated in parallel, enabling better risk assessment and optimization




This shift from static to dynamic planning fundamentally changes how mining engineers approach their work. Instead of treating each design element as an isolated component, the parametric approach recognizes the interdependencies between development drives, stopes, ventilation systems, and other infrastructure.



Time Efficiency Gains in Mine Planning



The parametric approach delivers substantial time savings compared to conventional methods. According to Ludwicki, the software &#8220;cuts weeks off design timelines&#8221; and allows engineers to &#8220;test 10, 20, even 30 design scenarios in the time it used to take for one.&#8221;



This efficiency gain transforms the design process from a bottleneck into a strategic advantage, enabling mining companies to:



Design TaskTraditional ApproachWith Parametric DesignKey BenefitInitial design creationWeeks to months of manual draftingDays to weeks with parametric templatesFaster project initiationDesign modificationsManual redrafting of affected areasAutomatic propagation of changesImmediate response to new informationScenario evaluationLimited by time constraintsMultiple scenarios evaluated simultaneouslyBetter decision-makingDesign optimizationIterative manual processSystematic exploration of optionsSuperior final designs



The ability to rapidly iterate designs means that engineers can explore more options and make better-informed decisions before committing to development plans that will ultimately cost millions to implement underground.



What Mining Problems Does Underground Designer Solve?



Underground mining operations face numerous challenges that impact productivity, safety, and profitability. GEOVIA Underground Designer addresses several critical issues that have traditionally hampered efficient mine planning and development.



Addressing Key Industry Challenges



How Does It Handle Design Flexibility?



Underground mining operations frequently encounter unexpected geological features, changing economic conditions, and evolving production requirements. GEOVIA Underground Designer addresses these challenges by:




Enabling rapid redesign when new information becomes available, such as updated 3D geological modeling



Preserving design intent while accommodating changes to key parameters like stope dimensions



Providing tools to test multiple scenarios against various constraints, including geotechnical limitations



Maintaining design coherence across complex underground infrastructures even when significant changes occur




Ludwicki emphasized this flexibility benefit, noting that &#8220;That flexibility enables better decisions based on real constraints like changing cut-off grades or unexpected geological structures.&#8221; This adaptability is particularly valuable in underground mining where geological uncertainty is an inherent challenge.



Can It Improve Collaboration Between Teams?



The cloud-based platform facilitates:




Real-time collaboration between geologists, engineers, and planners across different locations



Consistent access to the latest design iteration for all stakeholders, eliminating version control issues



Permission-based editing to maintain design integrity while enabling appropriate input from various teams



Global accessibility for distributed teams, supporting modern work arrangements and multinational operations




The integration with the 3DEXPERIENCE platform allows mining companies to break down traditional silos between technical disciplines, creating a more cohesive approach to mine planning and development.



What Technologies Power GEOVIA Underground Designer?



The technological foundation of GEOVIA Underground Designer represents a significant transfer of proven engineering tools from aerospace to mining, bringing sophisticated design capabilities to underground operations.



The CATIA Connection: From Aerospace to Underground



GEOVIA Underground Designer leverages CATIA—Dassault Systèmes&#8217; advanced engineering design software that has been instrumental in developing complex aerospace projects like Boeing&#8217;s 777 and 787 aircraft. As Ludwicki explains, &#8220;This is aerospace-grade technology being tailored for mining. If you can model a jet engine, you can model a stope.&#8221;



This technology transfer brings:




Proven parametric modeling capabilities from aerospace engineering, adapting precision design tools for mining



Robust mathematical foundations for complex spatial relationships that accurately represent underground environments



Sophisticated constraint management systems that ensure designs remain viable as changes are made



Advanced visualization capabilities that improve understanding of complex underground layouts




The adaptation of aerospace design principles to mining represents a significant advancement in how underground operations are planned and developed.



The 3DEXPERIENCE Platform Integration



As part of Dassault Systèmes&#8217; broader ecosystem, Underground Designer benefits from integration with the 3DEXPERIENCE platform, providing:




Seamless data flow between different mining disciplines, from geology to production planning



Version control and design history tracking that maintains a clear record of design evolution



Cloud-based accessibility and scalability that supports teams of any size and geographical distribution



Comprehensive permission management to ensure appropriate access to design elements




This integration creates a collaborative environment where all stakeholders can work together effectively while maintaining data integrity and security.



How Does Implementation Work in Real Mining Operations?



While the technology offers significant advantages, implementing GEOVIA Underground Designer requires thoughtful planning and a transition period for mining teams.



Adoption Strategy and Learning Curve



While the technology represents a significant advancement, implementation requires:




A mindset shift from traditional CAD-based workflows to parametric thinking about design relationships



Understanding of input-output relationships in design elements to effectively utilize the parametric capabilities



Training on the parametric modeling approach, though Ludwicki notes that &#8220;once users grasp the parametric logic – that everything&#8217;s an input or output – it becomes intuitive&#8221;



Customization of templates to match specific mining methods and operational requirements




Mining companies that invest in proper training and implementation support can accelerate the adoption process and maximize the benefits of the parametric design approach.



Case Study: Block Cave Mine Design



A recent implementation demonstrated the software&#8217;s capabilities when applied to a complex block cave mining operation:




Complete parametric model created in under two weeks, according to Ludwicki



All design elements (rings, access points, infrastructure) maintained parametric relationships



Design changes implemented in minutes rather than weeks, enabling rapid iteration



Multiple production scenarios evaluated against various constraints to optimize the mine plan




Ludwicki highlighted the efficiency gains, noting, &#8220;It took under two weeks, and everything – every ring, every access point – was parametric and simulation-ready. In the past, that could&#8217;ve taken months.&#8221;



What Makes Underground Designer Different from Traditional Mine Planning Software?



The shift from conventional CAD-based mine planning tools to a parametric design environment represents a fundamental change in how mining engineers approach their work.



Comparison with Conventional Approaches



FeatureTraditional Mine Planning SoftwareGEOVIA Underground DesignerDesign updatesManual, time-consuming redrafting of affected areasAutomatic propagation of changes throughout the designDesign relationshipsStatic, disconnected elements requiring manual coordinationDynamic, interconnected components with maintained relationshipsScenario testingLimited by time constraints, often only one or two options exploredMultiple scenarios evaluated in parallel, enabling better decisionsCollaborationFile-based, version control issues commonCloud-based, real-time updates accessible to all stakeholdersCustomizationLimited scripting capabilitiesVisual scripting engine for automation of repetitive tasksIntegrationOften standalone solutions with limited data exchangePart of comprehensive mining ecosystem with seamless data flow



Ludwicki emphasized this distinction, noting, &#8220;That&#8217;s why I fell in love with this technology – it&#8217;s fast, flexible and completely parametric. You change one element, and everything updates automatically. That&#8217;s a game-changer.&#8221;



The Virtual Twin Concept



GEOVIA Underground Designer lays the foundation for a comprehensive virtual twin of mining operations:




Digital representation that evolves with the physical mine, maintaining a current and accurate model



Ability to simulate operational changes before implementation, reducing risk and optimizing outcomes



Integration of real-time data to keep the model current with actual underground conditions



Platform for testing optimization strategies in a risk-free environment before committing resources




This virtual twin approach allows mining companies to make better-informed decisions and respond more effectively to changing conditions.



How Does Underground Designer Support Strategic Decision-Making?



Beyond the tactical advantages of faster design, GEOVIA Underground Designer enables better strategic planning and decision-making throughout the mine lifecycle.



Enabling Data-Driven Mine Planning



The software transforms the decision-making process by:




Providing quantitative comparisons between design alternatives based on key performance indicators



Enabling rapid assessment of economic implications for different development strategies



Supporting risk analysis through multiple scenario testing to identify optimal approaches



Facilitating optimization of development sequences to maximize net present value




Ludwicki highlights this strategic value, stating, &#8220;We&#8217;re helping clients get from strategy to operation faster and more accurately. We can simulate, evaluate, and adapt before committing millions of dollars underground.&#8221; This approach aligns perfectly with the growing emphasis on data-driven mining operations in the industry.



ESG Considerations and Sustainability



Modern mining operations face increasing pressure to improve sustainability metrics. Underground Designer supports these efforts by:




Optimizing development to minimize environmental footprint and reduce waste rock production



Reducing energy consumption through efficient mine layouts that minimize haulage distances



Enhancing safety through better planning of escape routes and ventilation systems



Supporting precision mining to reduce waste and water usage throughout operations




The ability to evaluate multiple design options quickly makes it easier for mining companies to identify approaches that balance economic performance with environmental and social responsibilities.



What Are the Implementation Requirements?



Successful implementation of GEOVIA Underground Designer requires appropriate infrastructure and organizational preparation.



Technical and Organizational Prerequisites



Successful implementation of GEOVIA Underground Designer requires:




Computing infrastructure compatible with 3D modeling requirements and parametric calculations



Network capabilities for cloud-based collaboration, though on-premises options are available



Training program for engineering teams to build parametric design competencies



Change management strategy for workflow transitions to minimize disruption




These requirements vary depending on the size and complexity of the mining operation, but planning for appropriate infrastructure and training is essential for successful adoption.



Integration with Existing Systems



The software is designed to work within broader mining technology ecosystems:




Data exchange with geological modeling software to incorporate updated resource models



Integration with production scheduling tools to optimize short and long-term planning



Compatibility with ventilation and geotechnical analysis software for comprehensive design evaluation



Connection to enterprise resource planning systems for budget and resource allocation




This integration capability ensures that the parametric design environment works seamlessly with other systems in the mining technology stack.



How Will Underground Mine Design Evolve?



The introduction of parametric design to underground mining represents the beginning of a broader digital transformation in the industry.



Future Developments and Roadmap



The parametric design approach represents the beginning of a broader transformation in underground mining:




Increasing automation of routine design tasks, freeing engineers to focus on strategic decisions



Integration of AI mining solutions for design optimization based on multiple constraints



Enhanced simulation capabilities for operational forecasting and risk assessment



Expanded integration with IoT and real-time monitoring systems to create true digital twins




As Ludwicki notes, &#8220;This is just the beginning. We&#8217;ve built the foundation. Now, it&#8217;s about seeing how the mining industry takes it forward.&#8221;



Industry Adoption Trends



While still in early deployment, the technology is positioned to become an industry standard as:




Mining companies seek competitive advantages through digital transformation initiatives



Engineers demand more efficient tools to address increasingly complex operational challenges



Operations require greater agility in responding to market changes and production pressures



ESG considerations drive more precise and optimized mine designs to minimize environmental impact




The mining industry&#8217;s growing embrace of digital technologies suggests that parametric design tools like GEOVIA Underground Designer will play an increasingly important role in future industry evolution trends.



FAQ: Common Questions About GEOVIA Underground Designer



How does the learning curve compare to traditional mining software?



While there is an initial learning curve associated with parametric thinking, most engineers become proficient within 2-4 weeks of training and practical application. The software includes templates and wizards to accelerate the transition. As Ludwicki points out, once users understand the parametric logic, the interface becomes intuitive and productivity increases rapidly.



Can existing mine designs be imported into the system?



Yes, the software supports importing conventional CAD designs, though maximum benefit comes from rebuilding designs parametrically to enable full flexibility. The import capability allows for a gradual transition as teams become more familiar with the parametric approach.



What mining methods are supported?



The software supports all major underground mining methods including longhole stoping, block caving, cut-and-fill, room and pillar, and sublevel caving through customizable templates. These templates provide starting points that can be modified to match specific operational requirements.



How does it handle complex geological constraints?



Geological structures can be imported from standard modeling software and used as constraints within the&nbsp;parametric mine design&nbsp;environment, ensuring development avoids problematic zones. This integration allows engineers to respond quickly when new geological information becomes available.



Is cloud deployment mandatory or can it be installed on-premises?



While cloud deployment offers maximum collaboration benefits, on-premises installation options are available for operations with connectivity limitations or specific security requirements. This flexibility allows mining companies to implement the solution in a way that matches their IT infrastructure and security policies.



Source: Discovery Alert, September 2025











Community is a place for GEOVIA users – from beginners to experts and everyone in between – to get answers to your questions, learn from each other, and network.&nbsp;Join our community to know more:



GEOVIA User Community&nbsp;–&nbsp;Read about industry topics from GEOVIA experts, be the first to know about new product releases and product tips and tricks, and share information and questions with your peers. All&nbsp;industry professionals are welcome to learn, engage, discover and share knowledge to shape a sustainable future of mining. &nbsp;



New member?&nbsp;Create an account, it’s free!&nbsp;Learn more about this community&nbsp;HERE.
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      <title>
      <![CDATA[ Revolutionising Underground Mine Design ]]>
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      <link>https://blog.3ds.com/brands/geovia/revolutionising-underground-mine-design/</link>
      <guid>https://blog.3ds.com/guid/292190</guid>
      <pubDate>Wed, 17 Sep 2025 09:44:24 GMT</pubDate>
      <description>
      <![CDATA[ GEOVIA’s Underground Designer is bringing aerospace-grade automation and parametric precision to underground mine planning.
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      <![CDATA[ 
GEOVIA industry process expert Christina Ludwicki for Australian Mining. 



In underground mining, where time is money and precision is paramount, even minor design errors or delays can have costly consequences. But what if redesigns could take minutes instead of months?



That’s the promise of Dassault Systèmes’ new GEOVIA Underground Designer role.



At the core of this innovation is parametric modelling – a powerful design methodology long trusted by industries like aerospace and automotive. Now, Dassault Systèmes is applying the same precision and flexibility to the mining sector.



Dassault Systèmes GEOVIA industry process expert Christina Ludwicki has been deeply involved in developing and adapting this technology for underground mine planning.



“I come from underground mining and have spent months on a single design, only for it to be changed and thrown away,” Ludwicki told Australian&nbsp;Mining.



“That’s why I fell in love with this technology – it’s fast, flexible and completely parametric. You change one element, and everything updates automatically. That’s a game-changer.”



Underground block cave mine design created parametrically.







Traditional mine design is notoriously time-consuming, involving manual updates and often disconnected&nbsp;workflows.



GEOVIA Underground Designer leverages CATIA, an engineering and design program behind Boeing’s 777 and 787 aircraft, to offer a dynamic, parametric design environment.



“Everything is connected,” Ludwicki said. “If I change the length of a heading or the position of a point, all the related infrastructure – stopes, drives, raises – update in real time. That ability alone cuts weeks off design timelines.”



This isn’t just about speed, it’s about enabling mining engineers to explore multiple strategic options quickly.



“You can now test 10, 20, even 30 design scenarios in the time it used to take for one,” she said. “That flexibility enables better decisions based on real constraints like changing cut-off grades or unexpected geological structures.”



While the role’s capabilities are advanced, Ludwicki said ease-of-use remains front of mind.



“It does require a mindset shift from traditional workflows,” she said. “But once users grasp the parametric logic – that everything’s an input or output – it becomes intuitive.”



The visual scripting engine adds further customisability for power users, allowing teams to build automated workflows tailored to their specific methods, whether it’s longhole, block caving or cut-and-fill.



“You don’t need to go deep into scripting if you don’t want to,” Ludwicki said. “There are simple tools for everyday use. It just depends on what problems you want to solve.”



GEOVIA Underground Designer doesn’t just build static plans, it creates fully parametric models, so any updates – whether due to a new fault, changed production targets, or updated geotechnical data – can be incorporated&nbsp;instantly.



“This is the foundation of a virtual twin,” Ludwicki said. “A design that evolves with your mine, and that reflects real-time decisions and inputs.



“And because it’s cloud-based, everyone – from engineers to analysts – can collaborate on the same up-to-date&nbsp;model.”



Collaborate with teams globally across mining value chain with the 3DS platform







The cloud-based 3DEXPERIENCE platform allows teams to work together globally. Permissions can be set, changes tracked, and visualisations shared instantly across the value chain.



While the Underground Designer role was only officially released in July, its technology has been stress-tested through years of development and internal use.



“This is aerospace-grade technology being tailored for mining,” Ludwicki said. “If you can model a jet engine, you can model a stope.”



She points to a recent block cave model built entirely using the new tools.



“It took under two weeks, and everything – every ring, every access point – was parametric and simulation-ready. In the past, that could’ve taken&nbsp;months.”



As the industry embraces automation, virtual twins, and ESG-driven efficiencies, Ludwicki sees Underground Designer as the logical next step.



“We’re helping clients get from strategy to operation faster and more accurately,” she said. “We can simulate, evaluate, and adapt before committing millions of dollars underground.”



While still in early deployment, Dassault Systèmes is actively seeking strategic partners to adopt and refine the&nbsp;technology in real-world&nbsp;environments.



“We don’t expect everyone to jump in blindly,” Ludwicki said. “This is new tech for mining, and we want to work hand-in-hand with clients to build the right models for their challenges. Once the framework is there, it’s yours to tweak, update and evolve as needed.”



For mines navigating tighter margins, ESG requirements, and shifting production targets, GEOVIA Underground Designer offers a rare combination of speed, accuracy and&nbsp;adaptability.



“This is just the beginning,” Ludwicki said. “We’ve built the foundation. Now, it’s about seeing how the mining industry takes it forward.”



With GEOVIA Underground Designer, the age of reactive mine planning may soon be behind us.



For those ready to embrace parametric tools and digital collaboration, the future is already here.



Source &#8211; Australian Mining, September 2025







Community is a place for GEOVIA users – from beginners to experts and everyone in between – to get answers to your questions, learn from each other, and network.&nbsp;Join our community to know more:



GEOVIA User Community&nbsp;–&nbsp;Read about industry topics from GEOVIA experts, be the first to know about new product releases and product tips and tricks, and share information and questions with your peers. All&nbsp;industry professionals are welcome to learn, engage, discover and share knowledge to shape a sustainable future of mining. &nbsp;



New member?&nbsp;Create an account, it’s free!&nbsp;Learn more about this community&nbsp;HERE.
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      <![CDATA[ How a Unified Design Environment Speeds Up Mine Design ]]>
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      <link>https://blog.3ds.com/brands/geovia/how-a-unified-design-environment-speeds-up-mine-design/</link>
      <guid>https://blog.3ds.com/guid/291448</guid>
      <pubDate>Wed, 27 Aug 2025 10:59:07 GMT</pubDate>
      <description>
      <![CDATA[ A unified design environment greases the gears and removes the friction between individual components of the mine design process, allowing for rapid updates across upstream and downstream workflows and easy team collaboration. Plus you can run all the ‘what if’ scenarios you want.
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      <![CDATA[ 
By @Chawki JREIGE, GEOVIA Senior Industry Process Specialist for AusIMM Bulletin. 



A unified design environment greases the gears and removes the friction between individual components of the mine design process, allowing for rapid updates across upstream and downstream workflows and easy team collaboration. Plus you can run all the ‘what if’ scenarios you want.



Strategic mine planning&nbsp;and pit design sit downstream of a host of other necessary tasks, such as resource modelling and geostatistical analysis, and upstream of still more tasks, including scheduling. As a result, when drilling triggers updates to geological and resource models, those updates then trigger changes to pit optimisation, which trigger changes to pit design, which trigger changes to scheduling. And it is these changes that can singlehandedly clog up the gears of the&nbsp;mine design process.



The issue with traditional data management



With traditional, independent data management, each change has to be repeated in and across each workflow. Take pit and phase optimisation, for example, intended to find the most efficient and profitable pit shape and mining sequence.



With&nbsp;GEOVIA Pit Optimizer, this workflow starts by integrating the envelope optimisation with the mine design, then moves on to aligning the mining schedule to maximise the net present value of the project, evaluating results from various mining scenarios, assessing the risks, and determining the most resilient operational strategy. Results from each step in the pit optimisation workflow inform the next step.



But what if a metal price suddenly goes up or down? A change like that is easy to deal with: just adjust the value of nickel or gold or copper, hit the go button, and re-run the step.



Figure 1. Optimised pit shells created with Pit Optimisation.







But when the members of a mine planning team are independently managing their own data, often using different software solutions, that change is not automatically communicated to the &nbsp;next engineer or geologist in line. Instead, each must re-do their step in the workflow every time an input changes to ensure the pit shells and reports, schedule and outputs, etc., are accurate and up-to-date. This is both labor-intensive and time-consuming.



There is, however, a proven method to remove the friction between individual components of the design process. It starts with moving to a unified design environment, where all data resides in one place, and everyone works within that same place.



Managing the design becomes a matter of managing inputs



A unified design environment, like the&nbsp;3DEXPERIENCE platform we use, is organised around parametric design. In this type of design, all inputs and outputs are stored as parameters. For pit optimisation, for example, these parameters include the pit wall slope angle, bench height, metal content, mineral prices, processing costs, scheduling and geotechnical considerations, and so on.&nbsp;More than that, however, the parameters could also be 3D objects, such as pit shells, or even other parameters or formulas.&nbsp;



This parametric organisation in turn compels a linear association or dependency between upstream and downstream tasks, where a change made anywhere by anyone within the unified design environment can (either automatically or by the click of a button) be updated across the workflow and either produce a new optimisation or update an existing one.



In other words, with parametric design, the pit design is aware of the pit shell. If the pit shell is updated, a quick re-run of the pit design will ensure all parameters, including the pit shell change, are applied. In this way, the inputs of each step of the optimisation will actually be the outputs from the prior step.



But the ability to make rapid changes upstream and downstream is not the only benefit of a unified or parametric design environment.



Two additional benefits



What creates a unified design environment is not just the interface or the platform. It’s also the data — for example, the block model used by the geologist will be the same type of block model used by the scheduler — and the metadata, such as who created or updated the design and what comments or objects are associated with it.



Having the metadata is particularly useful. It means that, when I come up with a design, a plan, or a schedule, I can associate tasks, such as peer review, with that output. In that case my colleague will automatically know when it’s time to comment on my work, or to approve it and pass it along to the next level.



Another significant plus is that managing inputs as parameters within a unified design environment also allows me to group inputs together in collections of parameters called scenarios.&nbsp;From there, I can copy a collection, modify the design by just one or multiple parameters, and perform a ‘what if?’ comparison between the scenarios.



How all this works in a unified environment



If I’m a planning engineer and I want, say, to generate toes and crests for specific mine designs using GEOVIA Surface Mine Designer, the workflow is more or less as follows.



I first choose a pit shell to which the design should conform, then apply certain parameters, like bench height, berm width, projection angle, etc.&nbsp;I then decide whether I want some (or all) changes, like bench height or angle, to be updated automatically, in which case the design will update itself as soon as I hit okay, or whether I want to make some (or all) changes manually.



Figure 2. Toes and crests of a pit design automatically generated to conform to an optimised pit shell.







If I make that second choice, any non-automatic changes will accumulate until I press the go button. This is particularly helpful if you are making lots of little changes and don’t want the design to update itself every single time: it’s up to you to determine when you are ready to see the cumulative effect of all the changes.



When I decide I’d like to to compare one design scenario to another, I can then drop it into a process composer simulation. Let’s say I want to see what happens to the design if the nickel price per pound changes.



First, I decide how I want that input/parameter to change and how many iterations I want to run: for example, to go up or down by 25 cents in value and to complete 100 iterations. The optimiser will then change that input as specified, execute the workflow with 100 incremental changes, collate the results, and present them to me for analysis at the end. I can compare the design scenarios and select the one that best helps me in my hunt for the optimal pit shape and mining sequence.



In a nutshell



By compelling a linear association and a sequence of tasks, a&nbsp;unified design platform with parametric design&nbsp;as its organising philosophy reduces the friction in the design process.



Because every piece of data in the platform understands every other piece of data, updates based on upstream changes are rapid, which makes it easier for everyone downstream to do their work: strategic mine planners can quickly update a pit optimisation and strategic mine plan whenever the resource model changes, while mine designers can quickly update pit designs based on newly created optimised pit shells. And everyone can experiment by creating scenarios (collections of parameters) and comparing the effects of changes — reducing the time required for design analysis.



Figure 3 | Automatically generated toes and crests of a pit incorporating a ramp with switchbacks. 







Source: AusIMM Bulletin, August 2025







Community is a place for GEOVIA users – from beginners to experts and everyone in between – to get answers to your questions, learn from each other, and network.&nbsp;Join our community to know more:



GEOVIA User Community&nbsp;–&nbsp;Read about industry topics from GEOVIA experts, be the first to know about new product releases and product tips and tricks, and share information and questions with your peers. All&nbsp;industry professionals are welcome to learn, engage, discover and share knowledge to shape a sustainable future of mining. &nbsp;



New member?&nbsp;Create an account, it’s free!&nbsp;Learn more about this community&nbsp;HERE.
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      <![CDATA[ Can Advanced Algorithms and Parametric Modelling Transform Your Mine Planning and Design? ]]>
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      <link>https://blog.3ds.com/brands/geovia/can-advanced-algorithms-and-parametric-modelling-transform-your-mine-planning-and-design/</link>
      <guid>https://blog.3ds.com/guid/287431</guid>
      <pubDate>Mon, 16 Jun 2025 09:12:40 GMT</pubDate>
      <description>
      <![CDATA[ A modern workflow that integrates parametric mine design, advanced optimization algorithms, uncertainty and risk analysis, cloud-based collaboration and integrated sustainability considerations is redefining strategic mine planning. This integrated approach streamlines pit and phase optimization, design, scheduling, scenario analysis, and cross-functional collaboration. 
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      <![CDATA[ 
By Cristian Poblete, Senior Manager, GEOVIA R&amp;D Apps Portfolio for Mining Magazine



A modern workflow that integrates parametric mine design, advanced optimization algorithms, uncertainty and risk analysis, cloud-based collaboration and integrated sustainability considerations is redefining strategic mine planning. This integrated approach streamlines pit and phase optimization, design, scheduling, scenario analysis, and cross-functional collaboration. The result: reduced engineering effort and more robust plans that deliver measurable increases in net present value (NPV), while enhancing design precision and operational feasibility.



Evolving Challenges and Trends in Mine Planning



Planners increasingly prioritize faster, more adaptable mine plans, but achieving them has historically proven challenging. Optimization algorithms have evolved significantly, shaping both traditional methods, such as pit and phase optimization followed by scheduling, and more modern methodologies like direct block scheduling (DBS). While distinct in execution, both trends ultimately converge on similar challenges: producing practical, actionable results and doing so rapidly. For example, traditional methods often relied on manual or automated evaluations of revenue factor ranges, frequently leading to outputs that were difficult to operationalize and required multiple iterations. Meanwhile, modern approaches like DBS enable temporal pit extraction directly but still struggle to translate results into practical, implementable phases. When considering the need to better understand the sustainability impact of mining operations, the challenges become increasingly complex.



Integrating Strategic Planning and Design: A New Framework



Dassault Systèmes proposes an integrated framework that unifies strategic mine planning and design into a continuous, collaborative process. The framework consists of seven interrelated stages, including risk and uncertainty analysis, and leverages advanced algorithms, parametric modelling, and cloud-based data environments. Together, these components support a more adaptive, data-driven, and analytically rigorous approach to mine planning and execution.



Figure 1: New interface that integrates optimization parameters, phase designs, and results display in 3DEXPERIENCE







Step 1: Early-Stage Optimization with Advanced Algorithms



Strategic planning begins with advanced optimization algorithms that generate initial pit shells, identify optimal phases, and evaluate scheduling scenarios. Techniques such as the updated Pseudoflow algorithm and direct block scheduling (DBS) enable rapid exploration of alternatives while honouring operational constraints and folding in sustainability considerations.



Step 2: Practical Phase Generation and Evaluation



Regardless of whether traditional methods or modern approaches like direct block scheduling (DBS) are used, planners face a common challenge: generating phases that are both practical and fast to produce. Dassault Systèmes addresses this with purpose-built tools and algorithms that create phase geometries in minutes. These tools account for operational parameters such as minimum mining widths, slope angles, size constraints, mining directions, and environmental factors, enabling planners to efficiently generate and compare multiple viable scenarios and select those offering the highest value and feasibility.



Step 3: Parametric and Generative Design Modelling



Once optimal phases are selected, parametric modelling technologies enable mine designs to be built and updated automatically based on defined rules and parameters. These tools minimize manual effort by automatically propagating changes across all design components. Generative design complements this process by allowing planners to explore multiple design variants driven by performance objectives and operational or sustainability constraints. Together, these approaches ensure a seamless, scalable, and sustainable transition from optimization to design.



Figure 2: Parametric design allows changes to be propagated to any element of the design, including ramp properties.







Step 4: Integrated Data Management and Collaboration



All planning activities occur within a unified, cloud-based platform where block models, design parameters, and scheduling inputs are fully interconnected. This associativity ensures that changes made in one area can be reflected, propagating changes throughout the process, reducing errors and improving consistency. Teams collaborate in parallel, with real-time access to shared data and a single source of truth, enhancing coordination and accelerating decision-making across functions.



Step 5: Schedule Optimization Based on Operational Designs



The GEOVIA Mine Maximizer(GMX) engine—an advanced implementation of the Bienstock-Zuckerberg algorithm enhances strategic scheduling by enabling the evaluation and optimization of complex, multi-period scenarios. It efficiently manages precedence and capacity constraints, generating high-quality schedules in minutes. This rapid feedback loop empowers planners to perform iterative updates and stay aligned with evolving business and environmental objectives and changing design inputs.



Step 6: Risk Analysis and Robust Mine Planning



Incorporating risk and uncertainty into the planning process adds analytical depth and supports more resilient decision-making. This stage applies techniques such as Monte Carlo simulations, Design of Experiments, and sensitivity analyses to evaluate a wide range of scenarios and strategic options. Automating these analyses allows planners to explore hundreds of scenarios interactively and assess their impact on project feasibility. This approach helps identify robust strategies that perform effectively under varying conditions enhancing confidence and improving overall project reliability.



Case Study and Results



This case study evaluated whether the integrated framework combining advanced optimization algorithms, parametric design, and cloud-based data management could deliver measurable advantages over traditional methods. The results were compelling.



Compared to conventional approaches, design time was reduced from hours to minutes, and overall project execution time decreased by 70%. For a 20-period project with two million blocks, phase optimization was completed in about five minutes, scheduling in under ten, designs with ramps in roughly thirty minutes per phase, and design changes and updates in less than a minute to regenerate the design.



Improved optimization through rapid scenario analysis led to NPV increases of 5% to 25%, depending on project complexity and constraints. Economically, integrating advanced tools including the updated Pseudoflow algorithm, fast phase generation, parametric design, and GMX scheduling unlocked value increases reaching hundreds of millions of dollars.



Additional Benefits: This integrated framework also delivers key advantages:




Reduces deviations from planned designs by generating realistic, executable phases.



Supports sustainable planning by embedding ESG metrics directly into cost models and constraints.



Improves collaboration and operational efficiency through a unified, cloud-based platform that gives all stakeholders access to a single source of truth.




Conclusions



The integration of advanced optimization algorithms, parametric and generative design technologies, and collaborative cloud-based data environments represents a paradigm shift in mine planning. These technologies reduce engineering time, elevate design quality, and unlock substantial economic value while fostering sustainability and cross-functional collaboration. By adopting this integrated framework, mining companies can better achieve their financial targets and adapt quickly to changing conditions. Most importantly, these innovations don&#8217;t replace the expertise of mine planners they amplify it, enabling professionals to focus on high-value, strategic decisions that drive long-term success.



Source: Mining Magazine, June 2025







Community is a place for GEOVIA users – from beginners to experts and everyone in between – to get answers to your questions, learn from each other, and network.&nbsp;Join our community to know more:



GEOVIA User Community&nbsp;–&nbsp;Read about industry topics from GEOVIA experts, be the first to know about new product releases and product tips and tricks, and share information and questions with your peers. All&nbsp;industry professionals are welcome to learn, engage, discover and share knowledge to shape a sustainable future of mining. &nbsp;



New member?&nbsp;Create an account, it’s free!&nbsp;Learn more about this community&nbsp;HERE.
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      <title>
      <![CDATA[ Mining Reimagined with 3DEXPERIENCE Platform ]]>
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      <link>https://blog.3ds.com/brands/geovia/mining-reimagined-with-3dexperience-platform/</link>
      <guid>https://blog.3ds.com/guid/283164</guid>
      <pubDate>Thu, 08 May 2025 18:05:38 GMT</pubDate>
      <description>
      <![CDATA[ At Dassault Systèmes, we are shaping the future of the mining industry and redefining its value. This is reflected in the technological solutions we provide to address global challenges, applying a thoughtful approach and vision that connect all stakeholders within the social and environmental systems we depend on. We provide the building blocks for the Sustainable Mine of the Future by mitigating risks, minimizing environmental impact, and maximizing efficiency.
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      <![CDATA[ 
Authored by Ralph SMITH, GEOVIA Sales Expert &#8211; Management Director, for Australian Mining



Technology is reshaping the world, and the mining industry is no exception, with virtual twin technology at the forefront.



As the industry faces challenges such as declining ore grades, rising costs, and stricter environmental regulations, technology like Dassault Systèmes’ 3DEXPERIENCE platform is critical.



“Our platform connects all the data points across mining operations, ensuring that when something changes in one area, all other relevant processes are updated accordingly,” said Dassault Systèmes’ Global Sales Director, Ralph Smith. “This provides auditability, repeatability, traceability, and visibility, underpinned by governance tools to digitize the mining value chain.”







In mineral processing, virtual twins can be used to model equipment maintenance management software, simulate plant performance, and integrate data across the mining value chain.



“Whether it’s testing different processing parameters or predicting potential bottlenecks, the technology enables mining companies to make proactive decisions rather than reactive ones,” Smith said.




“We can model and simulate something before physically implementing it. For example, we can plan and simulate the mining production cycle and the beneficiation process. By connecting multiple disciplines, we can better understand our decisions to maximize value, extract more for less, and drive our sustainability and productivity ambitions.”




By simulating entire mining operations in a virtual environment, companies can optimize layouts, reduce waste, and minimize environmental impact before a single shovel breaks ground.



More significantly, virtual twins allow mines to align key performance indicators (KPIs) across different operational areas.



“What tends to happen is that geoscience, mine planning, and processing teams often work in silos, leading to inefficiencies,” Smith said.



“There can be confusion at the end of the month regarding KPIs and who did what.”




“A virtual twin connects these disciplines so that when someone makes a change, you can actually see the impact down the value chain.”




At the core of Dassault Systèmes’ virtual twin technology is data—accurate, real-time information that enhances decision-making.



Mining companies can integrate real-time data from sensors placed throughout their operations.



“For example, sensors in a copper deposit can scan material in a bucket as it’s being loaded, providing real-time analysis of its quality,” Smith said.



“That information is then integrated into the virtual twin, allowing operators to anticipate what’s going to the mill or stockpile.”



By feeding real-time data into the virtual twin, mining companies can better predict processing requirements, whether it’s adjusting crushing and grinding parameters or modifying reagent mixes for optimal recovery.



One of the biggest challenges in mining is ensuring alignment between blasting, material movement, and processing efficiency.



“A blasting engineer’s KPI is often to reduce costs, not necessarily to increase plant productivity,” Smith said.




“But if you spend 20 percent more on blasting and get a one percent improvement in plant throughput, the project value is far greater.”




Dassault Systèmes’ virtual twin technology helps mine operators bridge these gaps, optimizing every step from ore extraction to final processing.



“We can simulate how material moves through the processing plant, identifying bottlenecks before they happen,” Smith said. “It’s about connecting the dots across disciplines rather than optimizing individual silos.”



Dassault Systèmes has also explored the reprocessing of old waste dumps and tailings, helping miners extract residual value while mitigating long-term environmental risks.



“There are more projects revisiting old tailings because what wasn’t valuable 20 years ago is now economic at today’s commodity prices,” Smith said. “It’s not just about recovering more material; it’s also about reducing environmental liabilities.”



Dassault Systèmes is also integrating artificial intelligence (AI) into its virtual twin platform, further enhancing predictive capabilities.



Aura, an AI-powered virtual co-pilot, was unveiled by the company at the 3DEXPERIENCE World event in Houston, Texas, in February.



“It’s an intelligent conversational chatbot for mining operations, where you can ask questions, and it provides responses based on the available data,” Smith said.




“It can summarize information quickly and allows you to dive deep into data across the entire operation by learning, teaching, and performing tasks for you.”




By embedding AI into the system, Dassault Systèmes enables mining companies to continuously learn from past performance, refining their processes over time.



“The advantage of AI is that it can analyze vast amounts of data quickly, summarizing key insights while providing links to source information for deeper analysis,” Smith said.



Dassault Systèmes&#8217; Virtual Twin Experience offers innovative solutions for the mining industry, enabling companies to rethink models, processes, and business strategies to drive sustainable innovation. These cutting-edge tools allow users to develop and maintain cross-disciplinary virtual twins, transforming the future footprint of mining operations.



By integrating Virtual Twin technology, the mining industry can achieve greater efficiency, sustainability, and strategic foresight, setting new standards for operational excellence and environmental responsibility.



Source: Australian Mining, May 2025







Community is a place for GEOVIA users – from beginners to experts and everyone in between – to get answers to your questions, learn from each other, and network.&nbsp;Join our community to know more:



GEOVIA User Community&nbsp;–&nbsp;Read about industry topics from GEOVIA experts, be the first to know about new product releases and product tips and tricks, and share information and questions with your peers. All&nbsp;industry professionals are welcome to learn, engage, discover and share knowledge to shape a sustainable future of mining. &nbsp;



New member?&nbsp;Create an account, it’s free!&nbsp;Learn more about this community&nbsp;HERE.
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      <title>
      <![CDATA[ Eight Steps To Achieve Optimal Results From Your Grade Control System ]]>
      </title>
      <link>https://blog.3ds.com/brands/geovia/eight-steps-to-achieve-optimal-results-from-your-grade-control-system/</link>
      <guid>https://blog.3ds.com/guid/281009</guid>
      <pubDate>Wed, 16 Apr 2025 09:24:02 GMT</pubDate>
      <description>
      <![CDATA[ Grade control is an integral part of both open pit and underground mining operations. Monitoring ore quality while controlling the grade and variability of a deposit is essential for mining companies to maintain accurate grade information. This helps determine mine plans, resource deployment, and ultimately, the mine’s return on investment. 
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      <![CDATA[ 
Authored for&nbsp;AusIMM Bulletin&nbsp;by&nbsp;Stephanie PHILLIPS, GEOVIA Industry Process Consultant Senior Manager and an AusIMM Industry Partner.



Grade control is not merely the responsibility of geologists. It spans multiple stages of the mining value chain, including data collection, interpretation, modelling and the production of practical excavation plans. In addition, there may be stockpile sampling and checks at key points, including belt samples, truck samples, face samples and a daily/weekly/monthly reporting and reconciliation stage. &nbsp;



A well-implemented grade control system can help minimise dilution, maximise recovery, improve reconciliation between predicted and actual production, establish consistency of procedures, ensure continuity of knowledge, and increase collaboration between geology, planning and production. On the other hand, ineffective grade control can lead to a reduction in the overall efficiency and profitability of a mining operation.&nbsp;



Although every site defines grade control differently through tasks and processes specific to that operation, there are some general best practices to maximise efficiency and achieve the best results from your grade control system. &nbsp;



1. Establish a consistent, repeatable and customisable framework 



Proper planning is key to a successful grade control system. Establish step-by-step workflows and specific preset parameters in the early stages of the grade control planning process. This helps ensure consistency in routines and sets expectations around outcomes. As you move into later phases of the mining cycle, your framework can be adapted to meet the changing needs of your operation.&nbsp;



A simple menu-based interface with step-by-step workflows ensures a consistency of grade control procedures.&nbsp;



2. Document your workflows 



Once you have established your framework, create written step-by-step procedure documents. Not only does this allow you to validate your workflows and parameters with other departments and facilitate internal alignment, but it also helps provide training and reference material to grade control staff. &nbsp;



Make sure to regularly update your documentation as changes and refinements are made to the workflow. This will greatly assist in knowledge transfer resulting from resignations and retirements to new staff that require onboarding.&nbsp;



3. Validate your data 



Your grade control system is only as good as the data that enters it. Maintain good data hygiene by ensuring your data is valid and robust before incorporating it into your grade control system. This includes performing an effective quality assurance/manufacturing quality control software process to ensure accurate and reliable sample data. 



Sometimes this can be performed within the database itself upon entry of the data, depending on the platform you use. You’ll get the best results from automating the process to save time and reduce errors.&nbsp;



4. Enforce consistent interpretations across your team 



Consistency is essential when interpreting grade information. Any slight deviations in the rules and parameters used to delineate dig areas, for example, could have big consequences, potentially leading to increased ore loss and dilution. &nbsp;



Instead, grade information should be classified and coloured according to specific ranges and cut-offs to facilitate the interpretation process. To do this, you’ll need to establish specific guidelines and rules when delineating interpolation domains and dig limits. Depending on the software you use in your grade control system, this process can be automated.&nbsp;



5. Work from a single source of truth 



Too often, the latest grade control data is not readily accessible to all team members and departments. Rather, it’s maintained in a static document on a local hard drive. And even if the document is shared with relevant team members, it becomes outdated as soon as the original is updated.&nbsp;



Today, there are digital platforms that can ingest, integrate, or index data to ensure that all team members always have real-time access to relevant data. This visibility not only assists with internal validation and alignment, but it also improves and accelerates decision-making.&nbsp;



6. Facilitate collaboration 



Along with a single source of truth, collaboration between team members and departments is vital for making proper decision making. It’s best to have open lines of communication between all team members, whether they’re on the same team or not. Some advanced business platforms will have collaboration features built in that make this process a breeze. Even without this, it’s important to break down any silos that exist between departments and encourage team members to review documentation and provide feedback in an open and honest manner.&nbsp;



7. Centralise and structure your data storage 



It may seem basic, but make sure to establish structured data storage guidelines and effective file naming conventions. There’s nothing worse than data that can’t be found because of a messy file structure or a file name no one can interpret. Creating proper naming conventions will ensure consistency, improve searchability and enhance the accessibility of data. It also helps to enable automation, which can result in significant time savings for you and your operation.&nbsp;



Centralised and structured data storage and file naming conventions.&nbsp;



8. Don’t neglect reconciliation 



Finally, reconciliation is a must in any operation. On a regular basis (e.g., monthly or weekly), compare your actual production with the predicted results of the grade control system. If there are no issues, you can confidently move forward with your mine plan. If there are discrepancies, fine tune your workflows, parameters and settings to improve future grade and tonnage predictions. Regularly performing material reconciliation will help keep your operation on target and profitable while helping you adapt to any changes that may occur throughout the life of mine.&nbsp;



Consider an advanced business platform 



A well-functioning grade control system provides a clear understanding of grade variations and allows for improved decision-making to drive profitability.&nbsp;



With recent technological advances, it’s possible to find further efficiencies using a digital platform such as&nbsp;GEOVIA Surpac’s grade control system, which can simplify what can be a very complex process through automation in a step-by-step framework, resulting in significant time savings. A simple menu-based interface is easily configurable and ensures a consistency of procedures with centralised and structured data storage. &nbsp;



However you decide to manage your grade control system, make sure it’s consistent, well-documented, flexible and accessible to help minimise dilution and maximise ore extraction. &nbsp;



Find out more 



If you would like to learn more, please visit the GEOVIA website at&nbsp;https://www.3ds.com/products/geovia/surpac&nbsp;&nbsp;







Community is a place for GEOVIA users – from beginners to experts and everyone in between – to get answers to your questions, learn from each other, and network.&nbsp;Join our community to know more:



GEOVIA User Community&nbsp;–&nbsp;Read about industry topics from GEOVIA experts, be the first to know about new product releases and product tips and tricks, and share information and questions with your peers. All&nbsp;industry professionals are welcome to learn, engage, discover and share knowledge to shape a sustainable future of mining. &nbsp;



New member?&nbsp;Create an account, it’s free!&nbsp;Learn more about this community&nbsp;HERE.
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