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      <title>Thought Leadership</title>
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      <![CDATA[ Bridging Academia and Industry in Engineering Education ]]>
      </title>
      <link>https://blog--3ds--com.apsulis.fr/topics/workforce-of-the-future/bridging-academia-and-industry-in-engineering-education/</link>
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      <pubDate>Thu, 18 Sep 2025 12:24:37 GMT</pubDate>
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      <![CDATA[ 
The global engineering landscape is undergoing a profound transformation. Technologies like electric vehicles, robotics and artificial intelligence are not only reshaping industries but also redefining the core of engineering education. For educators, understanding these changes and preparing students to excel in this future is more critical than ever.



This post explores how cutting-edge technologies are driving change in engineering education. We will look at the unique challenges they present and the opportunities they create for educators and students to succeed in this evolving landscape.



The Key Challenges in Modern Engineering Education



Engineering education is experiencing a major shift as technology evolves at an unprecedented speed. Success now requires both strong theoretical knowledge and the ability to apply it to real-world problems. Academic institutions face several challenges as they adapt their engineering education programs to meet industry needs.



Balancing Theory with Hands-On Practice



One of the greatest challenges in engineering education is integrating academic foundations with practical experience. Programs must incorporate learning in areas like generative design, artificial intelligence and sustainable materials. This ensures students are not just learning theory but can also apply it effectively.



Shifting to a Problem-Solving Focus



Traditional textbook problems are becoming less relevant. The industry needs graduates who can tackle real-world projects. Modern engineering education must move toward curricula that foster critical thinking and innovation through hands-on, project-based learning.



Fostering Interdisciplinary Collaboration



Today&#8217;s engineering solutions demand collaboration across multiple disciplines. Whether in electric vehicles, autonomous systems or robotics, projects require a systems-thinking approach. Engineering education programs must break down silos and encourage teamwork between different engineering fields.



Cultivating Lifelong Learning



With industries advancing so rapidly, a degree is only the beginning. Graduates must be prepared to embrace continuous learning to remain relevant throughout their careers. A forward-thinking engineering education instills the mindset that learning never stops. By addressing these challenges, academic institutions can prepare graduates not only to enter the workforce but also to lead in shaping the future of engineering.



Virtual Twin Experiences: A New Frontier in Engineering Education



Virtual twin experiences, combined with industry-standard applications such as CATIA, SOLIDWORKS, SIMULIA and DELMIA, offer a &#8220;learning by doing&#8221; environment. They create realistic, hands-on learning environments that allow students to engage with the same technologies used by leading companies.



Traditional learning environments often struggle to connect theory with practice. Virtual twins—interactive digital replicas of real-world systems—are changing that. Unlike textbooks or standard simulations, virtual twins allow students to experiment, test designs and see the consequences of their decisions in a virtual setting. This immersive learning approach deepens understanding and fosters critical thinking. For future engineers, it’s not just about memorizing formulas—it’s about applying theory to solve real-world problems.



For educators, virtual twins offer new levels of flexibility. Whether the focus is on mechanical engineering, design or environmental management, this tool enables experiential teaching that equips students with industry-ready skills. This practical application is a vital component of a comprehensive engineering education.



How 3DEXPERIENCE Edu Transforms Engineering Education



Today’s engineers need more than theory; they need practical skills that align with industry expectations. 3DEXPERIENCE Edu partners with schools and industries worldwide to equip students and future engineers to thrive in a rapidly evolving landscape. Our goal is to prepare them to solve complex challenges and drive innovation.



Our approach focuses on:




Collaboration and Trust: We partner closely with universities to align curricula with evolving industry needs, ensuring engineering education stays relevant.



Curriculum Integration: We help embed industry-standard tools such as CATIA, SOLIDWORKS, SIMULIA and DELMIA directly into academic programs.



Skills Focus: We ensure graduates gain practical, job-ready competencies that employers are looking for.




Education Experiences Approaches



To help educators manage tight curricula while still delivering depth and relevance, 3DEXPERIENCE Edu offers a comprehensive suite of solutions called “Education Experiences.” These leverage industry-standard software applications coupled with realistic virtual twins of real-world systems. They are designed to be flexible, offering different learning approaches to enhance engineering education.



Horizontal Learning



This approach offers a broad view of engineering projects that integrates multiple disciplines. It fosters teamwork, communication, and systems thinking—skills essential for modern engineers. It mirrors how complex projects are managed in the industry today.



Vertical Learning



This approach provides a focused dive into specific disciplines. It gives students the opportunity to strengthen technical expertise in targeted areas, allowing them to build deep knowledge in a chosen field.



Through these initiatives, 3DEXPERIENCE Edu empowers educators to deliver impactful programs. We equip students with the knowledge and skills essential for success in today’s demanding engineering landscape.



The Future of Engineering Education Is Here



By bridging the gap between academia and industry, educators are shaping the next generation of engineers. Through innovative teaching methods and cutting-edge technologies, we can transform engineering education from a theoretical exercise into a powerful engine for developing real-world skillsets. These future engineers will become the driving force behind the next wave of technological advancements.




Read the whitepaper





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      <title>
      <![CDATA[ Praga Cars delivers the Bohema super sports car ]]>
      </title>
      <link>https://blog--3ds--com.apsulis.fr/industries/transportation-mobility/praga-cars-delivers-the-bohema-super-sports-car/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/274723</guid>
      <pubDate>Mon, 16 Dec 2024 13:43:46 GMT</pubDate>
      <description>
      <![CDATA[ Praga Cars have been manufacturing and developing high-performance sports and racing cars for private and professional racers for many years. The introduction of Praga Bohema represents a strategic step towards establishing Praga Cars in the world of super sports cars.
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      </description>
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      <![CDATA[ 
The new Praga Bohema sports car is the work of the Czechoslovak car manufacturer Praga Cars, a company with a rich history in the automotive industry dating back to 1907. Praga Bohema combines the brand&#8217;s historical legacy with modern technologies and innovations. The development of this supercar was driven by the desire to offer customers a unique combination of performance, luxury, and exclusivity. Bohema was designed to create a car that is not only fast and agile on the road or racetrack but also provides exceptional comfort and an adrenaline-pumping driving experience.







Chief Design Engineer Mr. Ondřej Chotovinský has extensive experience in the automotive industry. Throughout his career, he has participated in various projects for companies such as Ferrari, McLaren, Aston Martin, Gordon Murray, Honda, and London Taxi Company. On his journey, he’s the most grateful for the continuous opportunity to meet experts, innovators, and creatives with rich experience and unconventional ideas in the automotive industry. &#8220;I lead a team of passionate engineers responsible for a wide range of projects, from the conceptual phase through prototype production and testing to final production. Our engineering team closely collaborates with other departments, suppliers, and external specialists to integrate advanced technologies, materials, and innovative processes to ensure our solutions meet industry standards, fulfill high-quality requirements, and add value for our customers.&#8221;



Streamlining design and manufacturing



Praga Cars faced the challenge of unifying the various CAD systems the engineers were accustomed to using. Data work wasn’t yet fully optimized. Given the Praga Bohema project&#8217;s complexity, it was crucial to switch to a unified PLM/CAD system to streamline future development.



The transition to a new system usually requires time, training, and adaptation to new workflows. For CATIA on the 3DEXPERIENCE platform users, this transition is relatively smooth. However, for others accustomed to different CAD tools or those who have never worked with a PLM system, a new environment can initially be stressful. This change disrupts established workflows, potentially leading to a temporary decrease in productivity. To successfully overcome these challenges, we chose a strategy of gradual system implementation. This approach allowed us to handle gradual data integration better and minimize the risk of disrupting development.



&#8220;I first started working with the 3DEXPERIENCE platform on a project in Maranello in 2019. I was part of a small team where Ferrari wanted to test and evaluate the benefits of implementing the 3DEXPERIENCE platform into the development phase of a sports car. In addition to a more visually modern and attractive environment, we, as engineers, appreciated the improved user interface and straightforward integration with the PLM system. During the prototype phase, this solution significantly facilitated data navigation, saving precious time,&#8221; adds Chotovinský.




&#8220;After four years, we can say that the 3DEXPERIENCE platform has brought many quantitative advantages. The most significant include a 10-30% increase in engineer productivity and a 20-30% reduction in the conceptual cycle.&#8221; 



Ondřej Chotovinský, Chief Design Engineer, Praga Cars




The development department at Praga Cars has been using the 3DEXPERIENCE platform for four years now. The main reason for its implementation was to streamline collaboration and communication among engineers during the development of the Bohema supercar. This is crucial for startups, which often work in small teams and need quick and seamless information sharing. At the same time, it was necessary to set up basic methodologies for data and process consistency and integrity throughout the development.



For larger companies, implementing and using the 3DEXPERIENCE platform can be complicated due to the range of functionalities and organizational needs. This requires careful planning, user training, and adapting integration processes. &#8220;For our smaller team, the key challenge was retraining the engineers who initially used a wide range of CAD tools to a unified PLM system and adopting the platform as an efficient tool for future development. We overcame these challenges through a strategic approach and collaboration with TECHNODAT, which helped us successfully deploy the 3DEXPERIENCE platform and maximize its value.&#8221;



Today, they manage all development and production data in a single system. This has eliminated unnecessary administrative tasks, improved internal collaboration, and enhanced cooperation with suppliers, pushing the project toward successful implementation. 



What&#8217;s next for Praga Cars?



This year, Praga Cars aims to deliver several vehicles to its customers. Therefore, most of their efforts focus on final testing and the production phase. They need to set up manufacturing processes to meet deadlines and smoothly cover demand. &#8220;Once we manage to meet the expectations of our first customers, demand will increase, and we will start to see a return on our investments, allowing us to smoothly proceed to further steps and also transfer all of our experience into future projects in Praga.,&#8221; adds Chotovinský, reflecting on the future of Praga Cars.



This is a guest post from trusted Dassault Systèmes business partner, TECHNODAT.








Learn more about Dassault Systèmes Transportation &amp; Mobility Solutions





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      <title>
      <![CDATA[ Unlocking Value in Mining ]]>
      </title>
      <link>https://blog--3ds--com.apsulis.fr/brands/geovia/unlocking-value-in-mining/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/274447</guid>
      <pubDate>Mon, 02 Dec 2024 11:59:53 GMT</pubDate>
      <description>
      <![CDATA[ The bottom line is that a centralised system deployed either on premises or on cloud would make the execution of the company’s Disaster Recovery Plan way more straightforward compared with decentralised systems.
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      <![CDATA[ 
Gustavo Pilger, Dassault Systèmes, GEOVIA on the critical role of centralized data management for efficiency, security, and innovation in mining operations.



The rapid growth of data, driven by technological advancements, presents both benefits and risks. Consolidating and centralizing data management is important to enhance efficiency, cybersecurity, and business intelligence. We discuss the critical challenges and opportunities in managing data within the mining industry and also explore the role of Dassault Systèmes&#8217; 3DEXPERIENCE platform in enabling mines to optimize processes, ensure data security, and improve disaster recovery capabilities.



Q) Please outline the key challenges that the mining industry faces in managing, protecting, and storing data.



Data is part of the IP portfolio of a company (together with a range of assets).  Therefore, it should be managed as any other valuable asset. Over the last 2 decades in particular, with technology advancements and the advent of a range of sensors, we have seen an &#8220;explosion of data&#8221; across industries including mining. 



This brings opportunities and challenges at the same time. The opportunities are mainly associated with the potential to better understand processes enabling one to improve them with productivity and efficiency gains that often lead to cost savings.



To achieve this state, however, one needs to overcome a few challenges: from navigating through a plethora of data for extracting knowledge to cybersecurity risks that could expose corporations to significant financial losses. The ability to count with a range of data to unlock or optimize mining processes is great. 



However, one of the first challenges is to consolidate the data that is often captured and stored in different systems. Not only these data are stored in decentralised (local) disparate repositories, but these systems are administered by different people with different levels of responsibility and awareness when it comes to data integrity and related risks. 



So, it is important that data is properly stored and managed in a way that allows one to extract the most knowledge out of them while preserving its integrity and exposure.



Q) How should mining companies approach consolidating and centralizing their data management to enhance data security?



The first step towards data consolidation is to compile a data inventory across the mine including information about type, format, purpose, frequency of change, etc. This allows one to map out the data flow intra- and inter-processes across the mine to then assess what matters the most and where potential bottlenecks are in order to prioritise where to begin. 



Therefore, understanding the data ecosystem together with the impact they have across KPIs is key to drive change in this space.



All sorts of data are being collected from a range of equipment (including sensors) across the environment of a mine. Together with good, valuable data also comes noisy data &#8211; and lots of them.  



Therefore, ideally, the data collected across the mine not only needs to be federated (or consolidated), but also needs to be indexed, sanitized (filtering out the noise), and contextualized so that meaningful insights can start to be extracted for decision-making.  



This could be achieved with the adoption of a centralized system that allows ingesting data collected by equipment across the mine, as well as their management in a safe and secure environment. The Dassault Systèmes 3DEXPERIENCE platform offers this solution.



Q) What critical benefits do mines gain from centralizing their data management?



I think the ultimate benefit is about being in control of the data instead of data taking control! One can only improve what is measured and understood! 



A centralized platform that allows data federation, indexation, 3D contextualization, analytics and action management, all in a secure environment, puts you in control of your assets allowing to extract the most value out of them.




Also, typically with decentralised systems, a great amount of time is dedicated to finding the right data or the latest version of data to work with. This translates to enormous inefficiencies, errors, re-work, and frustration leading to employee disengagement creating a vicious cycle of inefficiency. On the other hand, a centralised system, with rigorous access control processes, eliminates these inefficiencies. 




Every employee has access to the right data, in terms of permissions and versioning for conducting his/her work. Every decision taken by employees is recorded and justified within the system providing an inherent layer of traceability and auditability. Other benefits include de-risking data integrity and exposure.



Q) Tell ua about the role of centralized data management in improving data analytics and business intelligence, and how this benefits mines and their personnel.



GEOVIA, a Dassault Systèmes brand, provides software tools that allow our mining clients to model and simulate processes and how they interact with adjacent (connected) processes before anything is actually built, in early project development phases, or to correct the train of action on projects already in production in order to keep chasing value while operating.



Since the underlying data is federated, indexed, standardized and contextualized in a safe and secured single repository, and systems are connected with input and output associated through common data models, one can test multiple hypotheses or scenarios in the virtual world (Virtual Twin Experience) to efficiently apply a given design or plan in the real world &#8211; eliminating unnecessary waste, reducing risk, minimizing material re-handling while maximizing productivity! 



Data is not only safe and secured, but it is indexed (for quick retrieval), standardized through semantic dictionaries and contextualized, enabling meaningful link and associativeness between processes and data.



It is this data associativeness combined with smart methods and algorithms that allows one to constantly chase value while in operation, adjusting to (previous) uncertainty and unplanned events (being of technical, mechanic, or of market nature). 



I’d like to emphasize that having this core data, industry knowledge and know-how supported by semantic dictionaries (ontologies) central to our business platform (3DEXPERIENCE) that is built on a multi-physics and multi-scale foundation allows us to go beyond Generative AI and Large Language Models (LLMs). 



With this core set of characteristics, what we offer instead is Industry Language Models (ILMs) that indeed leverage LLMs but are combined with ontologies and industry knowledge and know-how within a platform environment (3DEXPERIENCE) that inherently provides governance and traceability.



Q) Please explain the ways in which centralized data management enhances a mine’s disaster recovery capabilities and why this is critically important?



A&nbsp;decentralised data management system, with data fragmented and scattered across the corporation, would need to rely on systematic discipline by personnel in charge to regularly back up local stored data, which could be a challenge by itself. Therefore, it&nbsp;would make it really hard (if not impossible)&nbsp;to fully recover should a disaster were to occur.



Instead, a centralised system can be restored in a matter of hours in case of disaster. Of course, assuming appropriate levels of redundancy, training and protocols would be in place to allow minimum levels of disruption in case of disaster.



The bottom line is that a centralised system deployed either on premises or on cloud would make the execution of the company’s Disaster Recovery Plan way more straightforward compared with decentralised systems.



Q) Ultimately, how does centralizing data management improve both a mine’s cybersecurity and the safety of its employees?



Data centralisation enables to significantly reduce risks associated with data integrity and cybersecurity. Consolidating the data in a single repository reduces the risk of losing or corrupting data that otherwise would reside in local drives of desktop computers located across mine sites, or into laptops of those employees required to work on the data. 



Instead, on a centralised system such as the 3DEXPERIENCE, the right version of the right data is available at any time to the right people. Since 3DEXPERIENCE counts with a rigorous access control process, this means that data is made available to employees according to their roles and needs. 




For example, a Surveyor does not need access to sensitive data such as gold grades from core logging, while a Resource Geologist needs it as it is required for him/her to conduct their work. So, all this combined mitigates quite significantly risks associated with data integrity, exposure and cybersecurity.




For those who choose to embrace the cloud to store and manage data via a cloud provider, be assured that the risks are well managed. Risks are arguably better managed than in in-house data centres. 



This is because most cloud vendors, such as Dassault Systèmes, operate with heightened security practices tailored towards protecting their infrastructure, applications, and customer data. A good cloud provider will adhere to industry standards and best practices that include:




IOS 2700x standards, and in particular implementation Guide ISO 27002



NIST 800 series



OWASP (Open Web Application Security Project) methodologies



CobIT framework




Also, good cloud providers employ multiple, independent and redundant mechanisms at various levels to block attacks. These measures provide far better security than most organisations can provide for themselves.



Therefore, in terms of risk management, it is a win-win proposition for all, including corporations, employees, contractors, and customers.







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[ AI augments Engineers for Sustainable Innovation ]]>
      </title>
      <link>https://blog--3ds--com.apsulis.fr/brands/catia/ai-augments-engineers-for-sustainable-innovation/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/274344</guid>
      <pubDate>Thu, 28 Nov 2024 14:59:56 GMT</pubDate>
      <description>
      <![CDATA[ For over 40 years, Dassault Systèmes, through its leading brand CATIA, has been at the forefront of industrial transformation and continues to be so today by using artificial intelligence (AI) to drive sustainable innovation.
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      <![CDATA[ 
How do we navigate AI for Industrial Transformation?



From design to industrialization, 80% of vehicles and aircraft today have developed their complete digital twin and now their virtual twin with Dassault Systèmes, especially with CATIA. Those solutions help the company extend its reach to other critical sectors, such as smart cities, energy infrastructures, and even the human heart.



AI serves not just as a tool for automation but as an enhancer of human capability, allowing engineers, designers, and architects to explore more innovative and sustainable solutions within development cycles. The core of AI lies in data, transforming it into valuable knowledge and expertise. This resembles a modern renaissance, where accumulated industrial know-how is made accessible across the entire product creation and industrialization value chain.




We are not automating to replace engineers, but augmenting their abilities to explore more innovative and sustainable solutions.Olivier SAPPIN, CATIA CEO








Virtual Twins: Bridging the Virtual and Real Worlds



Virtual twins are pivotal in integrating AI with industrial data, offering a comprehensive digital representation of physical assets. By creating virtual twins of products such as vehicle batteries, Dassault Systèmes with the 3DEXPERIENCE platform enables detailed simulation and testing in a virtual environment, reducing the need for costly and time-consuming physical prototypes.



Detailed Simulation with Virtual Twins




&nbsp;Simulation and Testing: Virtual twins allow the simulation of product characteristics such as battery autonomy, heat resistance, and steering angle, predicting performance under various conditions.



&nbsp;Design Optimization: Engineers and designers can refine product designs virtually, enhancing efficiency and sustainability at the early concept before physical production begins.








This approach not only saves time and resources but also enhances competitive advantage by enabling rapid prototyping and testing.



AI-Driven Enhancements in Virtual Twin Solutions



AI is crucial for advancing virtual twin solutions. It provides predictive insights that accelerate design and decision-making processes. AI can foresee potential issues and optimize performance by capturing and analyzing data from both virtual models and real-world usage.



Predictive Capabilities




&nbsp;Rapid Prototyping: AI algorithms enable quick generation and testing of multiple design alternatives within CATIA



&nbsp;Risk Management: Predictive analytics help in identifying and mitigating risks in complex projects, ensuring timely and cost-effective delivery.













&#8220;AI allows us to explore solutions rapidly, providing insights that would traditionally take months to discover.&#8221;








One Single Source of Truth



For more than 13 years, Dassault Systèmes has introduced the 3DEXPERIENCE platform to capitalize on the potential of virtual twins. This data-driven platform elevates information to knowledge and expertise, making it accessible and reusable across various domains.



Some key features:




&nbsp;Data Structuring: Ontologies are used to intelligently structure data, enhancing its usability.



&nbsp;Integration of Real and Virtual Data: By combining real-world usage data with virtual models, the platform delivers comprehensive insights for decision-making.












Protecting Industrial Data in the Age of AI



Data protection is paramount as industries leverage AI for innovation. Data anonymization ensures that proprietary industrial knowledge remains secure while benefiting from AI advancements.



Data Security Strategies




&nbsp;Anonymization Techniques: Used in sectors like healthcare, these techniques protect sensitive data while enabling advanced simulations.



&nbsp;Proprietary Data Utilization: AI is trained on industrial data for the exclusive benefit of its originators, ensuring competitive advantage.




Ready to embrace the Generative Economy



Dassault Systèmes prepares industries for a generative economy, where the focus shifts from products to experiences, with a new factor in the balance: circularity. By leveraging AI and virtual twin technology, engineers and designers can innovate sustainably, reducing development cycles and enhancing operational excellence.




AI gives engineers superpowers to accelerate product development, reduce life cycles, and optimize production.Olivier SAPPIN, CATIA CEO








As industries face increasing demands for competitiveness and sustainability, adopting these advanced technologies becomes imperative. Watch our latest webinar to learn how you, as an industrial company, can harness generative AI for your business needs.



And explore how CATIA transform your design and decision-making processes by integrating AI and virtual twins into your operations.
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      <title>
      <![CDATA[ A New, More Strategic, Way to Mine ]]>
      </title>
      <link>https://blog--3ds--com.apsulis.fr/brands/geovia/a-new-more-strategic-way-to-mine/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/272787</guid>
      <pubDate>Thu, 14 Nov 2024 09:32:35 GMT</pubDate>
      <description>
      <![CDATA[ Mine planning concentrates on long-range production planning aimed at maximising the value derived from exploiting an ore deposit. However, by its very nature, because it is long-term, a mine plan can be affected by a variety of internal and external forces including, for example, increased knowledge of the orebody, unexpected staffing issues, technical advancements ,and changes in legislation, economy, and market.
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      <![CDATA[ 
Mining, like many industries, can be slow to change. We often stick to traditional processes far longer than we should because we are comfortable with them and don’t want to take the risk of trying out new ones. But that means we may also miss significant opportunities both to improve profits and increase sustainability.



A common refrain from mine planners is that they do not have enough time to look at all the possible options for a solution space, which leaves them with sleepless nights worrying about such questions as: How much value was left in the last untested cut-off grade or mining capacity limit? Which direction and sequence would have created the best schedule? Have we followed the pit optimisation angles closely enough?



The fact is, however, that this situation can be solved — and these important questions can be answered — if we adopt a different approach to strategic mine planning.



Strategic mine planning



Mine planning concentrates on long-range production planning aimed at maximising the value derived from exploiting an ore deposit. However, by its very nature, because it is long-term, a mine plan can be affected by a variety of internal and external forces including, for example, increased knowledge of the orebody, unexpected staffing issues, technical advancements ,and changes in legislation, economy, and market.



Strategic mine planning attempts to de-risk a mine plan, to make it flexible enough to adapt to changes as and when they rise.



Traditional approach



The traditional approach to developing a mine plan is to assess a mine project based on the net present value (NPV). That means the NPV, which is calculated by applying a rate to progressively discount cash flows based both on how much profit the mine project must make and on its risks, becomes the primary KPI for the mine plan and drives decisions about where to start the extraction and how to orient the sequence.



For open pit mines, mine planners traditionally define reserves using the Lerchs-Grossmann (LG) algorithm, which identifies an economic envelope (pit shell), constrained to maximum slope angles, that will maximise the total undiscounted cash flow. With that final pit identified, the planner builds a sequence to reach the final pit often by creating nested pit shells using the same algorithm but constraining the volume of the output envelopes or adjusting the block model valuation using revenue factors (RFs). To select a subset of the nested pits to serve as pushback expansions toward the final pit, the mine planner then calculates the preliminary schedules.



Issue with this approach



The issue with this traditional approach is that most of the time, the nested shells available for the planner to select as pushbacks are not operationally feasible, and that may in turn require:




mining multiple satellite pits in earlier periods of the life of the mine



having a large starter pit, even for small revenue factor increments



following a concentric sequence, which requires multiple mining fronts, and/or



awkward pushback shapes and sizes, which may be difficult to implement.




Often, the planner will try to override these issues by building some feasible pushback designs loosely based on a set of nested pit shells and by splitting and merging different envelopes. However, this often seals the decision to use a pushback sequence based on the RF-limited pit shells instead of looking for other possible sequences towards the same final envelope. Plus, as a side effect, because the traditional approach is based on maximising undiscounted cash flow for simulated price-levels through different RFs, there is no guarantee that the sequence obtained will maximise NPV and could be out of alignment with other feasibility-focused KPIs.



A more flexible approach



Using process-automation tools with mine planning software allows mine planners to better appraise the optimisation solution space, delivering a workflow such as this:




1. Generate a ‘value map’ based on a modified pit optimisation algorithm that allows the planner to easily:





compare directional approaches while taking into account other vital components of a mine plan, such as spatial constraints, sinking rate and other feasibility KPIs as well as NPV.



identify the best starting region and corresponding directions, based on an assessment of preliminary strategic schedules for each combination, and




Figure 1. Optimised pit phases







2. Run thousands of possible scenarios based on mining rate and production capacity, their corresponding CAPEX and OPEX (making both the mine and the processing plant, and their corresponding costs, the right size), and cut-off grade, with each scenario producing its own mine plan and production schedule.



3. Optimise the schedule to maximise NPV by identifying what material to mine from each pushback and when, since the “what and when” will affect the mine’s order of revenues and costs (aka cashflow).



For example, the traditional approach has been to optimise the material send to the processing plant based purely on the mining and processing capacity. This can lead to low grade material taking up vital plant capacity in the early periods and reducing NPV among other KPIs.



A better approach would be to stockpile lower grade ore in the early years of production in order to prioritise higher-grade processing early on, and then use the remainder of the viable ore later, increasing NPV over the life of the mine. Even better still would be to not only optimise the processing capacity, cut-off grades, and stockpile usage, but to do this at the same time as choosing the sequence and the pit shells. This would free the optimisation to look at a wider solution space and not lock it in to decisions that were made in the previous step.



Figure 2. Strategic mine planning vision.







Strategic mine design



It is important to remember that optimisation and scheduling is only one side of the coin that is mine planning and that it takes a design to make a schedule actionable. In a process where we are creating large numbers of scenarios for optimisations and schedules, it is critical to establish a living design model with an&nbsp;intelligent workflow&nbsp;that updates as objects and inputs change.



Traditional CAD-based mine design works well but because it requires a designer to modify the entire shape of a design in response to a change, it is often slow, manual work that is prone to mistakes. This slowness can mean that a designer is able to produce just one or maybe two design options by deadline, with no time left for engineers to evaluate the integrity of the design.



Adding an automated parametric capability to the traditional design process not only ensures faster execution, it does so with improved accuracy and flexibility over traditional mine design.



Parametric design fundamentals



Parametric design&nbsp;does not produce a solution as much as generate a family of possible outcomes through dynamic automation.



Parametric modeling can use either a:




propagation-based system, where algorithms produce final shapes that are not predetermined by initial parametric inputs, or a



constraint system, where final constraints are set and algorithms define fundamentals (structures, material use, etc.) that satisfy these constraints.




Propagation-based systems often include ‘form-finding’ processes that optimise specific design goals against a set of design constraints, so that the final form of the designed object is ‘found’ based on these constraints.



Both types of parametric modeling have been used for years in other industries, such as civil construction, aviation, and manufacturing, as a replacement for traditional 3D CAD-based design.



Creating a living model



The parametric&nbsp;model-based approach&nbsp;incorporates traditional CAD functions but differs by adding links between objects and parameters.



This associativity preserves the connection between reference data — such as terrains and geology or resource models — and existing infrastructure models. This in turn allows the mine designer to update designs automatically every time there is new input data because, while the input data may have changed, the parameters of the design may not. The designer can also create templates by searching a series of functions&nbsp;and parameters, to speed up the time needed to design repetitive tasks, and deploy them manually or automatically through scripting.



The result is a “living” model where design changes made in a localised area will update the global mine design, and designs are ready for review days or even weeks faster than traditional practice allows.



Running limitless simulations



Mining projects are complicated, expensive, and extremely risky ventures. Being able to simulate everything from the&nbsp;mine design&nbsp;to the material movement in advance is critical to de-risking a project.



By&nbsp;automating the manual and iterative work done by the mine designer, parametric simulation enables the designer to compare the original design configuration with a larger spectrum of data. It works like this: regression models&nbsp;are first trained on simulation data and then progressively calibrated on measured data during a set monitoring period in order to (1) evaluate the&nbsp;robustness of design-phase performance and detect potentially critical assumptions, and (2) maintain a continuity with operation-phase performance with feed-back from measured data.



Applying simulations in real life



Parametric simulations can be used to design mining phases that consider unexpected variations and uncertainties, such as&nbsp;the metal content available in a mineral deposit and shifting commodity prices.



In the illustration below, we used a Design of Experiments (DoE) to perform a wide range of input modifications to a pit optimisation run. This allowed us to calculate tens of thousands of &nbsp;scenarios and explore the entire solution space, with the output being a dynamic set of pit shells linked to and associated with a set of pit design parameters. This associativity, coupled with parametric design, created the design shown below.



Figure 3. Optimised pit and haul road design.







The design now maintains a constant link with the optimisation results. As alternative scenarios are selected, new designs are automatically created and stored with their own revision and life cycle. We can also choose to link and associate them with other restriction criteria not made available to optimisation, such as pit crusher locations that require their own areas for infrastructure, flat areas in the ramp for regulatory purposes, or sump locations for pumping requirements. And we can assign a template to each of these criteria that is associated with the design and will be used to automatically update it.



Finally, each design can be used again within the life-of-mine scheduling, closing the planning loop and confirming the assumptions taken previously in the optimisation step.



Figure 4. Whittle and Process Composer Design of Experiments.







Conclusion



Strategic mine planning and parametric design are critical innovations at a time when mining companies are looking to reduce time to market and address marginal economic deposits, social, and ESG challenges.



If we can reduce our reliance on traditional mine planning tools and embrace new and innovative technologies, we will find the opportunities we need to move forward into a secure and responsible future.







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[ Q&amp;A: How GEOVIA is Reimagining Mining Efficiency ]]>
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      <link>https://blog--3ds--com.apsulis.fr/brands/geovia/qa-how-geovia-is-reimagining-mining-efficiency/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/272597</guid>
      <pubDate>Tue, 12 Nov 2024 18:29:05 GMT</pubDate>
      <description>
      <![CDATA[ The mining industry is on the cusp of a digital revolution. GEOVIA, a company with a long history in 3D design and geological modeling, is at the forefront of this change. By leveraging the power of parametric design and virtual twins, GEOVIA is helping mines operate more efficiently and sustainably. Company CEO, Mauro DELLEMONACHE explains how this technology is transforming the way mines operate, from reducing environmental impact to optimizing resource extraction.
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      <![CDATA[ 
GEOVIA CEO, Mauro DelleMonache in conversation with Lindsey Schutters, editor at Bizcommunity.com



The mining industry is on the cusp of a digital revolution. GEOVIA, a company with a long history in 3D design and geological modeling, is at the forefront of this change. By leveraging the power of parametric design and virtual twins, GEOVIA is helping mines operate more efficiently and sustainably. Company CEO Mauro DelleMonache explains how this technology is transforming the way mines operate, from reducing environmental impact to optimizing resource extraction.



So, you primarily serve the mining industry? What kind of solutions do you offer?



Yes, mining is our focus. We&#8217;ve been helping the industry visualize and manage resources for a long time. This includes everything from underground deposits to pit design, all brought to life in 3D and virtual twins. Traditionally, we offered desktop-based software for mine engineers and geologists.



You mentioned an evolution from desktop applications to cloud-based solutions. Can you elaborate on that?



Over the past few years, we&#8217;ve been aligning ourselves with the cloud revolution. Cloud computing offers vast storage and processing power, allowing us to run more complex simulations. This is key for the future of our technology. One of the biggest benefits is the concept of a &#8220;single source of truth&#8221; &#8211; a consistent, secure, and collaborative model accessible to everyone involved in a project.



Transitioning to the cloud sounds like a significant undertaking. How did you manage the switch, and what are the challenges for the mining industry?



It&#8217;s an ongoing process. Internally, we&#8217;ve had cloud capabilities for a while, serving various industries that have readily adopted cloud-based solutions. However, the mining industry presents unique challenges. Many mining operations are remote and conservative, making them hesitant to move data off-site.



How do you convince these cautious mining companies to embrace the cloud?



Education plays a big role. We showcase the benefits of the cloud, including reduced infrastructure and maintenance costs. We&#8217;ve even seen instances where clients initially requesting on-premise deployments ultimately opted for the cloud after considering bandwidth and overall cost efficiency.



What is the impact of the PGM (Platinum Group Metals) crisis on digital adoption in mining?



The PGM crisis is a major challenge, but it also highlights the need for Africa to position itself for the future. While short-term decision-making based on commodity prices is common, a shift towards longer-term planning is crucial. GEOVIA&#8217;s technology can support this shift through data-driven insights and future-oriented resource management.



Digital twins sound fascinating. Do you help clients with the entire IoT network setup, or do your solutions integrate with existing ones?




As a software company, our core focus is not on building the entire IoT network for clients. However, we&#8217;re recognising a shift. Clients increasingly need more than just software implementation; they seek ongoing support throughout the digital journey. My team has strong domain expertise, and we&#8217;re adapting to offer consultancy services alongside software deployment. This ensures clients get the most out of our technology.




For instance, one client expressed a clear desire for on-site support to leverage the full potential of our solution. This highlights the need for a more holistic client engagement model, going beyond just software sales and installation.



This comprehensive approach makes sense, especially considering the complexities of mine management. Will we see companies like yours embed more regional agents to cater to client needs?



Absolutely. The mining industry thrives on a local touch. While the industry is definitely moving towards automation with driverless trucks and other advancements, the human element remains crucial.




Interestingly, these technological advancements don&#8217;t necessarily reduce workforce needs. They create a demand for new skillsets, both within mining companies and in supporting industries.




We&#8217;re committed to deploying personnel to mine sites while leveraging technologies like our digital twins to maintain strong client engagement. Ultimately, the mining industry remains a &#8220;people business&#8221; where community plays a vital role.



Geologists using your software now need additional knowledge, perhaps even programming, to navigate local network issues. How is GEOVIA addressing this skills gap?



You&#8217;re spot on. This skills gap is a major focus for GEOVIA. One of our strategic priorities is building a robust education program with the future in mind.




We’re transitioning from selling desktop software to geologists to providing entire platforms that consider the geological model. This necessitates a shift in university curriculums to equip future professionals with the necessary skills. We can play a role in shaping these curriculums to prepare students for the evolving mining landscape.




AI disruption is a concern for many industries. How do you see AI impacting the future of your solutions?



AI, particularly large language models, has immense potential for training and education in the mining sector. However, deploying AI in real-world mine environments requires a science-based approach.



We can&#8217;t rely on a &#8220;black box&#8221; AI that makes decisions without scientific grounding. Explainability and adherence to first principles are crucial for trust in AI-powered solutions.



There&#8217;s definitely a place for AI optimisation, though. Imagine automating drafting tasks by feeding specifications into the system. We see this potential in our training business.



Instead of just selling software and offering basic training, high-quality content combined with a strong AI layer can provide a superior value proposition. Users can access information and support through AI-powered assistants exactly when they need it.



This highlights the exciting possibilities of AI integration within the technology stack.




Parametric design allows interconnected components within a model. Changes in one area automatically update other parts of the model, ensuring consistency. This approach is particularly valuable when combining multiple models to create a unique virtual twin




Did this require significant software development changes?



While leveraging existing algorithms, our development team had to recode them to enable parametric design functionality within the broader GEOVIA software suite. This is an ongoing process with new releases planned over the next few years.



How are you addressing latency challenges in remote locations?



We&#8217;re working with network providers to improve overall network robustness, but data sovereignty regulations are a major consideration. While Africa is a promising market, we need to achieve scale before deploying in-country servers.



Are you excited about new network opportunities like satellite deployments?



Our team is pragmatic. While these advancements are positive, security remains a top concern. We offer both cloud and on-premise solutions, allowing clients to choose based on their specific needs and security considerations.



How are you helping clients navigate environmental concerns and achieve their climate goals?



By optimising operations through simulation, technology can minimise unnecessary resource movement, leading to reduced environmental impact. Additionally, we&#8217;re exploring the concept of &#8220;virtualising&#8221; permitting regulations.



Imagine integrating regulatory data into the virtual twin, allowing real-time monitoring of adherence to environmental regulations. This &#8220;Sustainable Land Management&#8221; capability is still under development, but we&#8217;re seeking partners to collaborate on this project.



Can you elaborate on how real-time monitoring and &#8220;what-if&#8221; scenarios factor in?



The virtual twin allows clients to monitor operations in real-time and run simulations. These simulations can test various scenarios to ensure adherence to social licenses, environmental regulations, and profitability targets.



Who are your main competitors?



The competitive landscape is evolving. Traditional desktop software providers were once our main rivals. However, as we move into the digital twin space, collaboration with these companies becomes more relevant.



There&#8217;s a potential for combining our optimisation capabilities with the valuable data these competitors generate, ultimately benefiting the client.







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[ Mining Operational Excellence Through Digital Transformation with Dassault Systèmes GEOVIA ]]>
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      <link>https://blog--3ds--com.apsulis.fr/brands/geovia/mining-operational-excellence-through-digital-transformation-with-dassault-systemes-geovia/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/272433</guid>
      <pubDate>Mon, 11 Nov 2024 09:10:28 GMT</pubDate>
      <description>
      <![CDATA[ he mining value chain is a complex set of interlinked processes that involves many stakeholders from many different disciplines. To enable business transformation, it is paramount to approach the challenge from a standpoint that allows one to connect and interact in real (or near-real) time with people, processes, and technologies that make this chain of interlinked systems.
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      <![CDATA[ 
Article by Gustavo Pilger, WW GEOVIA R&amp;D Strategy &amp; Management Director, Dassault Systèmes.



The market for digital solutions has never been so competitive. Dassault Systèmes has been playing an important role in the technology journey, its industry-proven approach to breaking silos to bring people, processes, and technology together through Virtual Twin Experiences, leveraging a multi-scale and multi-physics (multi-domain) business platform (3DEXPERIENCE), is fundamentally what differentiates it from the competition. GEOVIA, a Dassault Systèmes brand provides end-to-end software solutions for mining, infrastructure, and urban planning environments to drive productivity, efficiency, and sustainability.




The mining value chain is a complex set of interlinked processes that involves many stakeholders from many different disciplines. To enable business transformation, it is paramount to approach the challenge from a standpoint that allows one to connect and interact in real (or near-real) time with people, processes, and technologies that make this chain of interlinked systems. This is what Dassault does. The company provides the path for its clients to realise business transformation. It provides software tools that allow clients to model and simulate processes and how they interact with adjacent (connected) processes before anything is built, in early project development phases, or to correct the train of action on projects already in production to keep chasing value while operating. This eliminates unnecessary waste, reducing risk and minimising material re-handling, while maximising productivity.








For example, how we can change the way we work by designing mines that extract more metal more efficiently and more sustainably (and at the same time comply with ESG standards and associated targets)? A Virtual Twin can help by modelling and simulating likely economic, environmental, and social scenarios for extracting ore to balance efficiency and cost with ESG performance. This enables users to identify their priorities and measure their performance/benchmarks to enhance responsible and sustainable growth. It allows managing permit status, asset agreements, asset licenses, and associated cost analysis, ensuring that everything goes according to plan and schedule.



Figure 1: Geology Modeler is an established role in the








Dassault recently introduced an additional role to its GEOVIA 3DEXPERIENCE portfolio: Strategic Mine Planner. This role complements the Pit Optimiser role, launched in December 2021, in order to allow the user to develop a comprehensive strategic plan that is robust and reliable, by conducting an evaluation of critical input parameters through multiple scenario analyses from development to closure. 




It allows users to simultaneously or sequentially apply several advanced value-adding options for optimising capacity to create an optimised and robust mining schedule that prioritises value and ecological responsibility. The main app of the role counts with a novel proprietary optimisation engine (GEOVIA Mine Maximizer – GMX) that is an extension of the Bienstock-Zuckerberg (2009) algorithm. GMX is the solution engine provided with Dassault’s Strategic Mine Planner and Pit Optimiser roles available on the 3DEXPERIENCE platform. It provides increased NPV while significantly speeding up runtimes when compared with commercial solution packages.




In February 2024, Dassault launched the Underground Mine Designer role. This role allows a user to rethink the design approach to underground mining through the evaluation of multiple options thanks to generative parametric modelling. One will be able to generate and evaluate multiple development designs through an automated parametric process, offering optionality assessment of designs. 




All that is within a ‘Safety by Design’ approach, allowing consideration of safety standards related to underground excavations from physical constraints to geotechnical features. In summary, the new Underground Mine Designer role will allow significant time savings and transparency through a seamless process and data model continuity between different mining levels, development areas, and practical access designs.



Additionally, in 2024 Dassault has planned four 3DEXPERIENCE releases, in which it will keep enhancing its two newly released roles, as well as its established 3DEXPERIENCE mining roles: Geology Modeler, Geoscience Referential Manager, Earth Engineering Coordinator, Pit Optimiser, and Surface Mine Designer.



In Surpac 2024, Dassault introduced four caving roles: GEOVIA Cave Footprint Finder, GEOVIA Cave Planning Manager, GEOVIA Cave Scheduler, and GEOVIA Cave Management System. These roles mirror those traditionally available in GEMS, which will eventually be discontinued. Therefore, going forward, GEOVIA’s solution for caving is through Surpac only – which is connected to the 3DEXPERIENCE through Dassault’s POWER’BY strategy.



In summary, in 2024 Dassault will continue to enhance and support its traditional desktop portfolio, build a new portfolio on a new and modern technology stack on 3DEXPERIENCE, and seamlessly connect its traditional desktop portfolio to 3DEXPERIENCE for expanding workflows and business processes.







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[ Optimizing Strategic Mine Planning with Simulation ]]>
      </title>
      <link>https://blog--3ds--com.apsulis.fr/brands/geovia/optimizing-strategic-mine-planning-with-simulation-2/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/272289</guid>
      <pubDate>Fri, 08 Nov 2024 10:59:36 GMT</pubDate>
      <description>
      <![CDATA[ Using Dassault Systèmes’ 3DEXPERIENCE platform miners can simulate diverse scenarios. Virtual twin technologies help test differing parameters and their influence on pit-optimized designs using generative design tools. Ultimately, the 3DEXPERIENCE platform helps extensively test different theories and operational strategies to assess their impact on project value.
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      <![CDATA[ 
By Ralph Smith, GEOVIA Sales Expert – Management Director, Dassault Systèmes



The mining sector in the Asia-Pacific faces significant challenges from geopolitical to market driven variations including price and energy costs that impact planning potentially leading to mine closures. A primary requirement for mining success is optimizing the strategic mine plan to ensure flexibility and robustness to secure value for investors, stakeholders, and communities. Strategic mine planning when optimized establishes short-term positive cash flow and profitability while achieving long-term objectives.



Addressing volatility through simulation



Price volatility is a common element of uncertainty in mining plans, which means the strategic mine plan should answer critical questions such as how do variations in elements like price impact operations? Answering such questions helps ensure that mines operate profitably and meet social and environmental norms when commodity or supply prices change. Given the extensive timeline from project inception to actual ore mining — often spanning 15 to 20 years — mining firms invest in ventures that may only begin to return on investment somewhere within this long timeframe.



It must also be remembered that only about 49% of mining pre-feasibility studies make it to a bankable feasibility study stage. In the pre-feasibility phase, if miners fail to grasp the full spectrum of opportunities for ore extraction, studies may need to be redone. Therefore, optimizing strategic mine planning aims to reduce such rework and increase the potential to progress to the next phase while improving the probability of faster progress with a deeper understanding of the impact of project drivers.



Acknowledging the pressing demand for minerals such as nickel, copper, and lithium for global energy transition plans, and the typical 15 to 20-year from discovery to production, miners are challenged to expedite the decision-making processes. It’s imperative to assess all potential risks, even with data containing lower confidence levels or with incomplete data at hand.



Delivering results with scenario simulation builds a complete view and helps identify opportunities to improve on the base case for a feasibility study. Evaluating risks, such as geotechnical challenges associated with pit slopes or grade variations with different confidence levels provides insights into the actual factors that might impact the project. Thus, simulating various scenarios and fully comprehending potential outcomes becomes central to refining the strategic mine plan.



3DEXPERIENCE platform: Enhancing simulation with virtual twins












Using Dassault Systèmes’ 3DEXPERIENCE platform miners can simulate diverse scenarios. Virtual twin technologies help test differing parameters and their influence on pit-optimized designs using generative design tools. Ultimately, the 3DEXPERIENCE platform helps extensively test different theories and operational strategies to assess their impact on project value.




For example, simulating various slope angles can reveal implications for waste disposal costs and efficiency; steeper slopes may reduce waste storage needs and associated costs.



Furthermore, by applying uncertainty to grade and production scale the virtual twin can model the effects of grade reduction on the mining plan and project lifespan. This information helps understand the impact on key financial metrics such as discounted cash flow, net present value (NPV), internal rate of return (IRR), and the mine’s potential lifespan and risk profile.



Design parameters for simulation can encompass production scale, fleet sizing, mining sequences, and extraction levels. External factors such as fluctuating prices and fuel costs, along with estimated ore grades, can also be fed into the system to simulate various scenarios. This comprehensive analysis helps prioritize strategic mine planning and identify high-value mining sequences early within the lifecycle to ensure faster cash flow.












Leveraging the 3DEXPERIENCE platform, companies can run thousands of simulations on hundreds of sensitivities, including mining direction, more swiftly than with traditional methods and tools.








The 3DEXPERIENCE platform provides a unified environment to connect processes and automation, facilitating the rapid assessment of numerous scenarios. This automation also supports strategically determining optimal production scales and mining phases while considering a wide spectrum of operational and capital expenditure variabilities.



Optimization through simulations helps refine strategies for mining phases, tackle production uncertainties to improve cash flow, and identify the best mining locations, while prioritizing high-value areas early. Strategic mine planning teams can run thousands of simulations calibrated for various sensitivities and external factors in a shorter period of time than current practices.



Targeting faster cash flows with the 3DEXPERIENCE platform




The 3DEXPERIENCE platform’s simulation capabilities enable mining companies to utilize ‘value surfaces’—to manage the volume of scenarios and visualize the impacts of parameter variation and their contribution to the outcome.




This approach optimizes strategic mining plans for cash flow, NPV, and IRR, bolstering confidence in mining operations and securing profitability. Additional attributes, such as ESG parameters or mill productivity, can be incorporated and simulated to assess outcomes.



Results from optimized mine plans improve productivity metrics, such as tons per kilowatt hour and potential CO₂ emissions, addressing Scope 1 environmental challenges and aligning with ESG benchmarks crucial for financing mining operations.



The 3DEXPERIENCE platform integrates mining processes, breaking down silos to enhance value while helping achieve sustainability and compliance targets. It offers a comprehensive risk overview when compared to traditional mine planning. By simultaneously running simulations across various sensitivities and scenarios, and testing multiple inputs, the platform enables a more efficient and holistic planning process.



Automation within the 3DEXPERIENCE platform enhances transparency across strategic mine planning teams and stakeholders. Simulations reveal the impact of variables such as a 5 percent lower ore grade or lower productivity to adapt the plan to immediate and future challenges, including commodity price drops, supply chain constraints, or rising fuel costs, thereby safeguarding long-term profitability.



Enabling innovation in mining with seamless collaboration



The 3DEXPERIENCE platform layers simulation capabilities on top of the existing engine or mining technologies, allowing for data to be universally accessed by employees of all profiles and disciplines through the simulated output which becomes a single source of truth. This approach democratizes data and promotes informed decision-making at all levels of expertise, skill and domain.



The power of the solution lies in its ability to run hundreds to thousands of simulations for multiple sensitivities and external factors. All while seamlessly connecting multiple disciplines and department silos, providing a holistic view of the consequences from various decisions effects on a unified project flow sheet.



The data model integrates the inputs of metallurgists, mine planners, and geoscientists into one workflow ensuring everyone has a comprehensive view of their decisions’ real impacts. This seamless collaboration across disciplines fosters innovation and delivers improved value for investors, stakeholders, and the community while ensuring digital transformation and modernization of mining operations.







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[ Maximizing Mining Value with the 3DEXPERIENCE platform ]]>
      </title>
      <link>https://blog--3ds--com.apsulis.fr/brands/geovia/maximizing-mining-value-with-the-3dexperience-platform-2/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/272265</guid>
      <pubDate>Thu, 07 Nov 2024 18:22:37 GMT</pubDate>
      <description>
      <![CDATA[ The platform integrates and automates mining processes, dismantles silos and enables executives to focus on higher-value areas and optimized geotechnical, economic, productivity and ESG parameters. The optimization ensures positive cash flow or net present value (NPV) while adhering to sustainability and compliance goals.
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      <![CDATA[ 
By Ralph SMITH, GEOVIA Sales Expert – Management Director, Dassault Systèmes



Traditionally, mining processes were manual, with strategic planning conducted by engineers across various disciplines using Excel while managing data in silos. The Dassault Systèmes’ 3DEXPERIENCE platform leverages the existing mining engine to introduce a cloud-based simulation layer on top of it to democratize data.



The platform integrates and automates mining processes, dismantles silos and enables executives to focus on higher-value areas and optimized geotechnical, economic, productivity and ESG parameters. The optimization ensures positive cash flow or net present value (NPV) while adhering to sustainability and compliance goals.



Offering a comprehensive, multidimensional risk overview, the 3DEXPERIENCE platform exceeds traditional manual planning methods. Miners can run thousands of simultaneous simulations across different sensitivities and scenarios, testing multiple inputs for a more efficient and comprehensive planning approach.



Automation via the 3DEXPERIENCE platform increases transparency in strategic mine planning. Simulations reveal the effects of variables and help adapt strategies for the present and future challenges, addressing issues such as price variations, supply chain interruptions, rising fuel costs and ESG to secure immediate cash flow and long-term profitability.



Three case studies illustrate how the 3DEXPERIENCE platform enables miners to pursue value continuously.



Optimizing reserves and strategic mine planning



A greenfield mine in the Asia-Pacific region mines 72 thousand tons of copper and gold ore per day. The challenge was pinpointing the optimal mining footprint by evaluating various production and development rate scenarios, aiming to align reserves with ideal mine size, production targets, and development rates.



The overall goal was sustainable results, optimizing key economic indicators such as net present value (NPV), internal rate of return (IRR), and capital expenses within the strategic mine plan.




Using the 3DEXPERIENCE platform, the company managed to optimize reserves across different cutoff levels, deprioritizing lower-value areas to focus on higher-value regions earlier in the project, thus securing faster and more assured cash flow.








The company refined their strategies by simulating diverse production plans, incorporating varying inputs alongside different development rates and production targets. They conducted 500 realistic simulations within just 16 hours, which increased the NPV by 35 percent over the base case.



They also identified several high-potential production and development rate scenarios as attractive alternatives, significantly benefiting the bottom line and enhancing the long-term sustainability of the strategic mining plan.











Solving multi-pit challenges



For a greenfield open pit mine mining between 62 to 100 million tons per annum of copper and gold, the challenge was to boost the operation’s viability and strengthen confidence in its long-term potential.



The project included three mines sharing a single process system. Early on, it was crucial for the company to identify optimal reserves and establish mine-friendly design phases. Determining the best production scale for each mine and pinpointing the optimal pre-stripping investment were key challenges. A critical task was also finding the most suitable location for the processing plant and maximizing the NPV of the strategic mine plan for the entire mining complex.




By leveraging the 3DEXPERIENCE platform, the company effectively navigated these challenges, identifying the best phases and production scales by considering all cost options, including capital and operational expenses, along with pre-stripping investments. The platform also facilitated the identification of the optimal plant location.








By analyzing 75,000 simulations over just five weeks, the company achieved a 42% increase in NPV compared to the base scenario, significantly enhancing the bottom line and solidifying confidence in the mine’s long-term viability.



Reducing stripping ratio and costs and enhancing NPV



The project involved a brownfield open pit mine that extracts 56 million tons of iron ore in the Asia-Pacific region per annum. The engagement with Dassault Systèmes using the 3DEXPERIENCE platform aimed to increase project potential, enhance decision-making confidence, and evaluate expansion alternatives.



The main challenges included optimizing the planning for two mines sharing a process plant but constrained by transportation methods for concentrates, simplifying phase design, and accurately assessing the impact of enhanced production under varying market conditions. Additionally, resolving production interruptions presented another significant challenge, emphasizing the need for robust operational strategies.




The 3DEXPERIENCE platform enabled the company to optimize reserves, enhance phasing, and reduce costs. The operation sequence of the two pits was refined, and to decrease the stripping ratio, 30,000 simulations were conducted for multiple inputs within just a month.








Ultimately, the stripping ratio at the first mine was reduced by 16%, and at the second mine by 24%. Cash flow at the second mine increased by 29% to US$146 million, while at the first mine, it increased by 42% to US$85 million. An increase in NPV to US$231 million was also achieved.



The 3DEXPERIENCE platform is pivotal in running thousands of simulations with limited initial data to establish a solid base case for a bankable feasibility study, delivering accurate and realistic results.



The platform facilitates the simulation of various theoretical scenarios and understanding their potential impacts, and it is essential in dynamically refining the strategic mine plan throughout the project’s life. This approach ensures the project’s short-term profitability and long-term sustainability, aligning with ESG standards.







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;



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      <![CDATA[ How Cooperation Leads to Greater Efficiency and Faster Decarbonisation ]]>
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      <link>https://blog--3ds--com.apsulis.fr/brands/geovia/how-cooperation-leads-to-greater-efficiency-and-faster-decarbonisation/</link>
      <guid>https://blog--3ds--com.apsulis.fr/guid/272251</guid>
      <pubDate>Wed, 06 Nov 2024 21:07:39 GMT</pubDate>
      <description>
      <![CDATA[ A world-wide switch to electric vehicles is generally acknowledged as a fundamental component of decarbonisation. However, while demand for energy-dense batteries continues to soar, limited availability of the raw materials they require, such as lithium, nickel, and cobalt, is creating a major supply chain bottleneck — a bottleneck that threatens to impede their widespread adoption.
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      <![CDATA[ 
Authored by Garrett Kramer, GEOVIA Technical Executive, and Paul ABONGWA, GEOVIA Industrial Process Consultant, Dassault Systèmes



The ever-increasing demand for critical minerals required to support global decarbonisation is placing great responsibility on mining companies to produce those minerals as quickly as possible. It’s a big ask. To achieve it, the mining industry will require a revolutionary level of technological cooperation from one end of the supply chain to the other, and beyond.



A world-wide switch to electric vehicles is generally acknowledged as a fundamental component of decarbonisation. However, while demand for energy-dense batteries continues to soar, limited availability of the raw materials they require, such as lithium, nickel, and cobalt, is creating a major supply chain bottleneck — a bottleneck that threatens to impede their widespread adoption.



The International Energy Agency estimates that at least 50 new lithium projects, as many as 60 new nickel mines, and up to 17 cobalt new mines must be developed by 2030 to meet demand. While these numbers may change – if solid-state battery technology matures quickly, for example, it will reduce the need for some metals – the reality is that the mining industry typically takes roughly 15 years to develop a new project from discovery to production. And that slowness may be contributing to some EV manufacturers bypassing traditional supply chains and engaging directly with mines to secure the primary materials they need through offtake agreements. These offtake agreements, in turn, indicate:




that the price of mining production is no longer solely governed by the commodities market



that mining operations must now be regarded as an integral part of complex and interconnected supply chains, and



that miners must be able to plug into the even more complex and technologically advanced supply chains of established EV and battery makers or they will lose market share.




The same pressure to develop projects as quickly as possible holds true for mines producing other materials as well, but environmental permits and all the other elements required for sustainable mining take the time they have to take, regardless of what is being mined.



Where we think it is possible for mines to move more quickly is within their own organisations by adopting technology that makes them internally more efficient while also helping them transfigure their supply chains, both to incorporate mining operations and to link to their customers’ currently more advanced supply networks.



The Key is Cooperation




We believe mining companies need to work more cooperatively than they are now, because cooperation leads to efficiency, efficiency leads to greater speed, and greater speed leads to faster decarbonisation, not only in e-product manufacturing but also in mining companies’ efforts to reduce their own carbon footprints.




Mining is a series of interlinked processes that begins with the process of securing permits, moves through the processes of exploration, development, and production, and ends with the processes of decommissioning and site rehabilitation. Each process requires its own system – its own working methods and principles and objectives – but all systems are ultimately working to reach the same overall goal and all depend on access to relevant and reliable data to make sound, well-informed decisions. Yet many mining companies today maintain their systems as distinct entities, each with its own data sources, data management procedures, and methods of communicating information.




Geology modeling, for example, is often viewed as separate from other mine systems, such as mine operations, beneficiation, logistics, marketing, and sales. However, the geology of a site is integral to every other systems because it influences not only drill and blast planning, but also excavation, loading, hauling, feeding, processing, and, of course, the end result: how much a mine produces and for how long.




Ensuring that the latest geoscience data can be easily shared among both geology team members and all other interconnected mine systems opens the door to the kind of end-to-end cooperation that reduces roadblocks and delays along the supply chain and provides a more reliable foundation for chain-wide decision making.



To illustrate how to create and support cooperation in and across mining systems, we use the GEOVIA Geology Modeler, which is based on Dassault Systèmes 3DEXPERIENCE platform, as an example. For simplicity&#8217;s sake in this article we will refer to this as &#8216;the Geology Modeler&#8217;.



The Geology Modeler



The Geology Modeler includes two applications essential to reliable geological data analysis: Geoscience Referential Manager and Geology Modeling, which uses implicit modeling.



Figure 1. Geology Modeler role on the 3DEXPERIENCE platform.







Implicit modeling employs mathematical algorithms to make use of all available geological data in interpreting the formation of surfaces, such as grade and faults, between known drill hole points. It can then rapidly build multiple 3D subsurface scenarios from that data, enabling geologists to examine more geologic possibilities then they could with explicit modeling workflows. But just as with explicit modeling, the reliability of those scenarios is entirely a function of the quality of the data entered into the model.



High-quality data requires:




Secure, effective data management



Comprehensive geological visualisation and analysis



Correct data interpretation, and



Precise model validation.




And the best way to ensure all of that is by using a single, platform-based, centralised repository in the cloud where all your mine’s geoscience data, in any format, can be integrated, stored, analysed, interpreted, and managed. This ensures geologists do not have to go from one application or file type to another to find relevant data, making it easier for them to &nbsp;identify critical trends and patterns and produce the most accurate geological models. A single repository also guarantees that the latest, most complete version of any data becomes the single source of truth for everyone (with the right permissions) to reference, even as multiple users work on the same data at the same time.




The Geology Referential Manager defines and &nbsp;manages all the geoscience reference data, structured and unstructured, that is collected by geoscientists, engineers, consultants, and contractors. This includes geological field observations, topographical point cloud, geochemical, lithological and remote sensing data, drill hole records, assays, etc. Immediately as new information is acquired, the Geology Referential Manager automatically updates the data across the platform, and anyone with access can see and use that updated data (the old data is not deleted, however; best practice is to allow complete traceability and auditability).




From that foundation of reliable data, geologists can then use the Geology Modeler to automate the creation of implicit geology models, without time-consuming wireframing. At the same time, because the Geology Modeler provides multiple functions, like meshing control lines and a broad range of parameter settings (such as dynamic anisotropy), geologists retain the control they need to represent the full array of in-ground conditions and geological structures that are essential for building a complete model (a virtual twin) of the geological asset. And because it also employs parametric design principles, those same geologists do not need to start again from scratch whenever new data comes in, reducing time and effort even more.



Creating Team Cooperation



In addition to saving time, here’s how using new technology such as the Geology Modeler &nbsp;also works to build new levels of cooperation.



Let’s say that your mining company is at the end of the exploration phase for a new mineral project. After you’ve compiled your exploration borehole database, received your assay results, etc., and stored all structured and unstructured resource definition data (including any existing explicit models generated by any software) on the integrated digital platform, where it has been defined by the Geology Referential Manager.




Your project manager: develops a project plan, creates a shared space on the platform for all team members involved in the project, where they all have access as required to the same set of applications, tools, and workflows, assigns each team member specific tasks and provides a timeframe for completing those tasks, and monitors project progress — including any bottlenecks — against the project plan using a number of different visual methods.





Each team member: receives an email indicating that they have been assigned a task, logs in to the platform, where they can drag and drop any data held on the platform or stored locally to begin work immediately, which, triggers automatic document versioning, data check-in/check-out, and user file and folder permissions to ensure traceability and auditability.




After the team has interpreted all structured and unstructured geoscience data, the assigned modeling geologist uses the Geology Modeler to create a geological model with traceable versioning over time. With the modeling done, the geologist updates the task as complete, which sends a message to the project manager. The manager can then review the model and the modeling process, request changes or approve the results, and share the model with the rest of the project team inside their collaborative space on the platform.



The team then moves on to validation, which may involve:




creating sectional views and conducting a visual analysis of the domains compared to the actual data



using query filters to test the model, and/or



sharing the model across the mine for collaborative peer review.




When the time comes to update the model with new information – new drillhole data, for example – the geologist authorised to make changes will:




review and validate the updated data



create an interpretation – for example, by producing a composite to use, either for a numerical interpretation or to adjust lithologies for a geological interpretation (or both at the same time)



make a copy of the old model to be updated (or simply create a new model)



define the geochronology, creates structural zones, and sets the parameters for how zones will relate to each other



generate an up-to-date geology model in a simple, repeatable process



return to the collaborative space, and



update the task as completed – all in a matter of minutes.




Creating External Cooperation



As soon as that new, up-to-date geological model is generated, it will be of interest to many of your mine systems and downstream processes.




For example, mine planners and mine engineers need to know about anything that may directly or indirectly affect how they schedule blocks for mining. Through the Geology Modeler, they can be included on any updates to the model that trigger material change and reclassification. Processing engineers or metallurgists also often need detailed information on expected ROM and feed — for example, to help investigate why and how deleterious elements or minerals will affect downstream processing.




This kind of operation and supply-chain-wide cooperation enables mines to better address issues and delays when they occur, reducing their impact on the business, and to take critical business decisions faster, making them more agile and efficient. Efficient enough, we think, to help reduce the time it takes from exploration to production, which can in turn help to spur decarbonisation at the mine and all the way along the supply chain.




Cooperation, however, is not limited to inside your own mining company or supply chain. You can also configure digital platforms to include external stakeholder communication and collaboration during the permitting process. And you can share all your models — geological models, resource models, tailing models, etc. — in varying levels of detail as required, from the high level of detail required by regulators to ensure compliance, to the lower levels of detail required by shareholders, investors, or local communities, leading to smoother communications, greater transparency and trust, and, again, more efficiency.




Another important bonus: a cloud-based platform also means that you will be able to immediately plug into the supply chains of established EV and battery makers or other potential partners as required, helping to stimulate decarbonisation world-wide.







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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