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Can digital twins help improve efficiency and cut costs as mining operators face a future of dwindling resources alongside challenges presented by deeper mines, rising energy costs and infrastructure shortages? #mining #digitaltwins #AI #automation #maintenance #miners #mines

💡 Digital twins are transforming maintenance and many other areas of the mining industry. In a recent article, Andy Tunnicliffe spoke to Catello (Lelio) Di Martino, head of network application research at Nokia Bell Labs about the potential of these AI-driven models, as well as some of the recommendations for adoption. “The primary role of digital twins in mining is to offer AI-powered data correlation, quantifying and predicting the impact of operational decisions across various dimensions to achieve planned business goals, such as the number of tonnes of ore produced per day,” Di Martino says. He points to several areas in mining where digital twins can optimise processes increase productivity, or improve safety including: ☑ blasting and drilling ☑ mine sustainability through the collection of actionable data on operational emissions, energy and water consumption ☑ training for remote operations. Read the full article now. Link in the comments 👇

The role of artificial intelligence in reshaping predictive maintenance in the mining industry. The mining sector is facing increased productivity pressure due to growing demand for clean energy minerals and supply chain diversification. To address these challenges, mining companies are rapidly adopting digital tools to boost operational efficiencies and transparency. Key Points: 1. **AI in Predictive Maintenance**: - AI is transforming predictive maintenance by allowing companies to track and monitor the performance of assets in real-time, shifting from reactive to predictive models. - AI collects and analyzes large amounts of data on mining assets, enabling companies to intervene before problems occur, thereby reducing costs and improving efficiency. 2. **Historical Context**: - Traditional maintenance models were based on preventative measures, which often led to unnecessary maintenance actions or missed critical issues. - Manual condition monitoring was limited and could not be done continuously, missing faults that deteriorate quickly. 3. **Advancements in AI**: - The rise of Industry 4.0 and sensor technology has made predictive tools smarter and more efficient. - AI can analyze vast amounts of data, providing real-time insights into operations and enabling better decision-making. 4. **Impact on Operations**: - AI has a "tremendous" impact on the mining sector, informing the development of smart factory tools like cloud computing and digital twins. - Digital twins allow for testing and monitoring of operational processes, enhancing the capability of predictive and AI modeling. 5. **Challenges**: - While digital tools are more accessible, there are still obstacles to their universal rollout across mine sites, including cost and skill requirements. 6. **Future Outlook**: - AI is expected to continue playing a crucial role in predictive maintenance, enhancing operational efficiency and safety in the mining industry. AI has a significant potential in improving predictive maintenance, which is essential for maintaining high productivity and safety in mining operations. Source: https://lnkd.in/dCCe8NJ6

👁️🗨️ In the mining industry, operational visibility is a game-changer. Industry 4.0 technologies, particularly Vision Computing, are providing mining operators with unprecedented insights into their operations. By leveraging advanced imaging and analysis, mining companies can now map entire hauling roads and identify obstacles that could hinder efficiency. 🚜 Enhanced visibility means operators can proactively address issues before they escalate. Did you know that Vision Computing can reduce unexpected downtime significantly? By pinpointing obstacles and optimizing routes, this technology ensures smoother and more efficient mining operations. 🌍 One of our clients has implemented Vision Computing together with Datacakra to monitor their hauling roads in real-time. This has led to improved resource allocation, reduced delays, and a significant boost in overall productivity. With better visibility, they can now make informed decisions that drive efficiency and safety in their mining operations.

Here are some technological trends that are shaping the future of mining: Automation of mining: To increase productivity while protecting worker safety, the mining industry is adopting automation. Artificial intelligence, robotics, and automation drive for increased productivity and more efficient processes. Autonomous machinery and mining software are used to track downtime, estimate costs and control quality. Adaptability: Flexible and scalable solutions are essential to meet changing challenges of the mining industry. Electrification: Using clean, renewable sources of energy contributes to reducing the carbon footprint. Continuity: Integrated and intelligent systems ensure smoother mining operations. Targeting: Rather than focusing on mine residue, the focus is on efficient extraction of minerals. What do you think are the benefits of this improvement in the mining industry?

𝗧𝗵𝗲 𝗺𝗶𝗻𝗶𝗻𝗴 𝗶𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗶𝘀 𝗲𝘀𝘀𝗲𝗻𝘁𝗶𝗮𝗹 𝗳𝗼𝗿 𝗮 𝗺𝗼𝗿𝗲 𝘀𝘂𝘀𝘁𝗮𝗶𝗻𝗮𝗯𝗹𝗲 𝗲𝗻𝗲𝗿𝗴𝘆 𝗳𝘂𝘁𝘂𝗿𝗲—but by 2030, mines will only meet 𝟱𝟬% of the cobalt and lithium needs and about 𝟴𝟬% of copper requirements. This resource deficit can be significantly reduced by integrating the latest digital technology to enhance the accuracy of mineral exploration and optimize production operations across the value-chain. 🎯   Microsoft solutions are at the forefront of this innovation, helping customers unlock opportunities with 𝗱𝗮𝘁𝗮, 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴, 𝗮𝗻𝗱 𝗔𝗜. Industry leaders like Boliden, Emirates Global Aluminium (EGA), Epiroc and Sandvik are leveraging Microsoft technology to 𝗶𝗺𝗽𝗿𝗼𝘃𝗲 𝘀𝗮𝗳𝗲𝘁𝘆, 𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆, 𝗽𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝘃𝗶𝘁𝘆 𝗮𝗻𝗱 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗺𝗮𝗸𝗶𝗻𝗴.   Find out more in Joseph Starwood's article: https://lnkd.in/ge2_6X4R

🌟 Transforming Mining with Digital Twin Technology 🌟 Digital twins are revolutionising the mining industry by creating virtual replicas of physical assets and processes. Several mining companies are already using digital twins to improve their operations. Key benefits of this technology are: 🔧 Real-time Monitoring & Predictive Maintenance ⚙️ Process Optimization 👷♂️ Safety & Risk Mitigation 🌱 Sustainability 💰 Cost Savings & Asset Longevity Nonetheless, there are challenges. Communicating clear benefits and aligning IT and OT teams effectively are crucial to avoid fragmented efforts and ensure successful implementation. Despite these challenges, embracing digital twin technology can lead to significant long-term benefits. For more insights, check out the full article below by Claudio Saes from Forbes Business Council.

Exciting developments in the mining industry! Darryl Willis shares how AI and digital transformation are driving innovation and sustainability. Key takeaways: Digital Mindset: Embracing a digital mindset is crucial for unlocking new possibilities with data, algorithms, and AI. Unified Approach: Collaboration and strategic AI integration are essential for overcoming industry challenges. Sustainability: AI is pivotal in creating efficient, resilient processes, addressing the critical minerals deficit, and supporting the energy transition. Read more about how AI is shaping the future of mining: From Mindset to Market: Driving AI Innovation and Sustainability in Mining #Mining #AI #AITransformation #EnergyTransition #Sustainability #Digital #DigitalTransformation #Innovation Per Christian Honningsvåg Hany S. Soliman Srikant Kadambi Sam Mathew Marc Gigon Torrie Turner, P.Geol Rabia Kamal Daniela Vargas Garcés Megan Smith Hanna Grene Darryl Willis Miki Usyak Rob Schapiro Rachel Hollander Bilal Khursheed Hema Prapoo Nick Parker

Integration of artificial intelligence (AI) and predictive maintenance in the mining industry. AI technologies are revolutionizing maintenance practices by enabling proactive and data-driven approaches. These technologies analyze vast amounts of sensor data to predict equipment failures before they occur, thereby reducing downtime and maintenance costs. The implementation of AI in mining also enhances safety by identifying potential risks early. While AI adoption in mining is growing, successful implementation requires overcoming challenges such as data quality and integration with existing systems. Overall, AI-driven predictive maintenance is poised to significantly improve efficiency and sustainability in the mining sector. https://lnkd.in/dbEd_Tkp

In the context of South Africa and Africa in general is this true: The mining industry has traditionally been reluctant to embrace new technologies. However, this is changing with a growing emphasis on digital transformation and advanced technologies. The industry now recognizes the importance of digitalisation for competitiveness and adapting to market dynamics, with a focus on real-time optimisation of processes. This shift toward digital transformation is not just about embracing new technologies but also about redefining the operational landscape of the mining industry. As this study delve deeper into the specific technologies being adopted, it becomes evident how automation, remote-controlled operations, and artificial intelligence are pivotal in enhancing productivity, reducing costs, and improving environmental efficiency. #AI #mining #environment #sustainability