rethink sustainability

    Panning for Gold With Artificial Intelligence

    Panning for Gold With Artificial Intelligence

    The mining industry has a problem. On the one hand, diminishing resources have led to decreased productivity while on the other, a growing clamour for a lower environmental footprint means operations must focus on sustainability.

    One solution has come in the form of artificial intelligence (AI) and its ability to make mining work in a much smarter way with the eventual result of helping the environment.

    The mining industry has a problem. One solution has come in the form of artificial intelligence (AI).


    The larger picture

    The earth is quickly running out of natural resources. Phosphorus, an essential element for plant growth, is at risk of running out in 50 to 100 years unless new deposits are found. Similar forecasts from BP hold true for oil and natural gas. In essence, the low-hanging fruit in the mining industry have long been picked.

    Rare earth metals, used to manufacture high-tech devices, are increasingly in high demand. Forecasts suggest that the market will cross $20bn by 2024. To satisfy some of that appetite, the industry is taking a look at deep-sea mining as a source for many of those elements, such as manganese and cobalt, which are used in a variety of applications from car phones to electric car batteries. Advocates argue that mining the sea floor, where there are substantial deposits, would be much more efficient than chasing after the last dredges of ore on the earth's surface following the law of diminishing returns.


    The sustainability equation

    The global demand for rare earths and minerals is not the only resources-related challenge facing the industry. Mining is also water intensive and this presents a problem in a world where, according to the World Meteorological Association, at least one in four people will live with chronic or recurring water shortages by 2050. So mining industry players must now not only find and extract diminishing amounts of resources, they must do it all sustainably — both on land and under the sea. The use of water in mining is being addressed by wastewater recycling solutions and in other creative ways. In Chile, floating solar panels sit on top of the wastewater reclaimed from mining and are expected to protect a large portion of it from evaporation. A greater proportion can then be reclaimed and reused, thereby decreasing dependence on fresh water.

    The global demand for rare earths and minerals is not the only resources-related challenge facing the industry. Mining is also water intensive.

    The increased recycling of resources, cordoning off areas of high environmental impact to minimise impact on wildlife and conducting and complying with independent environmental impact assessments are all ways to address the sustainability equation.

    The extraction of manganese nodules -an essential component in batteries for electric cars - from the sea presents a prime example of how the sustainability compromises might play out. Mining involves vacuuming the relevant area of the sea, collecting the nodules and then returning the rest back to the ocean floor. However, the process is extremely disruptive to wildlife which might get sucked up during the process and also get disturbed by the deposited sediments.

    Artificial intelligence to the rescue

    AI promises to be the panacea that addresses the sustainability equation largely by making the process more efficient.

    The mining industry is especially well suited to the implementation of the new technology, which essentially involves machines progressively learning from operating conditions over time. Adam Allouba, partner at the Montreal office of law firm Dentons, says mining operations are incredibly data-rich, which means plenty of raw material for algorithms to play with. “There's a huge amount of information that you can extract from a mining operation, whether it's exploration or production," Allouba says. “You can put sensors on pretty much every single piece of equipment when you're operating a mine and get a sense of a variety of parameters."

    AI promises to be the panacea that addresses the sustainability equation largely by making the process more efficient.

    That's exactly what the company DataCloud does. It places Internet of Things (IoT) sensors on the ends of drill equipment. These sensors measure acoustic waves as a way of predicting where ore deposits lie. Areas rich in ore will register a different wave pattern than those that are not. The sensors, in real-time, pick up these wave patterns and deliver the vital intelligence to operators. This in turn leads to more intelligent drilling. “By giving clients the insights into where the waste is and where the ore is, we empower them to run more productive operations," says Thor Kallestad, CEO.

    Areas rich in ore will register a different wave pattern than those that are not. The sensors, in real-time, pick up these wave patterns and deliver the vital intelligence to operators.

    Another industry trend that's driving the case for adoption of AI is the "deep need for newer and smarter ways of doing business" Allouba says. According to research from McKinsey, mining today is 28% less productive than it was a decade ago, which means more room for technologies such as AI that can fine-tune efficiencies across the board.
     

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    mining today is 28% less productive than it was a decade ago which means more room for technologies such as AI

    How AI is helping

    One of the biggest advantages of using AI through embedded sensors or other means is the access to real-time information. Even in deep-sea mining, using it to see where the actual deposits are leads to less dredging and more efficient extraction.

    Cynthia Younes, marketing manager at Newtrax, a digital company that optimises many aspects of underground mining including ore detection, says that shaving off even small inefficiencies in the industry can lead to big sustainability gains. For example, Newtrax's digital solutions, which are anchored in AI, can be used for predictive maintenance of machinery and evaluating conditions of underground mines. Based on this intelligence, mine managers can manage how they use labour resources and also nip machinery problems in the bud.

    Underground mining is also considered more sustainable than surface mining because it has a lower footprint than an open pit and it also selectively extracts only the ore. The industry has traditionally shied away from underground mining because of the difficulties involved in access but AI is changing that. “Investors tend to prefer surface mining. But if you're able to show them that with technology and data analytics we can make underground mining a lot more efficient, then there's going to be a cultural shift," Younes said. "And that's going to have a greater positive environmental impact as a whole."

    “Investors tend to prefer surface mining. But if you're able to show them that with technology and data analytics we can make underground mining a lot more efficient, then there's going to be a cultural shift," Younes said

    Autonomous vehicles, driven by computer vision and AI, are also helping in mining. “Whether you're hauling more ore-rich nuggets or gaining precious insight after drilling just a few exploratory holes, [artificial intelligence] means less destruction of the earth," Allouba said. "You're not removing soil or cutting down trees when there's no need for them." And that applies to dredging the ocean floor as well.

    As mining enters the next era where the competition for resources becomes ever more intense, it is facing increasing calls for lasting sustainable practices that incorporate an earth-friendly approach into its very DNA. AI helps mining and sustainability work hand in hand — and that is a win for all parties concerned.

    Important information

    This document is issued by Bank Lombard Odier & Co Ltd or an entity of the Group (hereinafter “Lombard Odier”). It is not intended for distribution, publication, or use in any jurisdiction where such distribution, publication, or use would be unlawful, nor is it aimed at any person or entity to whom it would be unlawful to address such a document. This document was not prepared by the Financial Research Department of Lombard Odier.

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