A recent report by EY identified several key risk areas for the mining industry in . But, as the report highlights, these potential risks can also become important opportunities for differentiation with the right approach and resources!
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Here's our overview of the top five mining-industry risks that we think can be turned into opportunities in ' and how we can help you make this transformation.
For these trends to become opportunities rather than risks, mining companies will need the right resources, tools, and partnerships. At Malvern Panalytical, we're here to provide some of those tools with our analytical instruments ' including automated process control solutions, instruments to support with environmental monitoring, and remote sensing tools for exploring new resources.
And we'll continue developing and improving these solutions with you, to pave the way for a more efficient, sustainable mining industry in and beyond.
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Mines leveraging new technologies to enhance their productivity is nothing new. A poll by Ernst and Young of more than 700 industry representatives revealed that the majority of the top mining businesses have already started their digital journey in some capacity ' notably through investing in autonomous and IoT-based technologies. But the big, forward-looking players who are on the road to innovation only make up around 10% of the mining industry, meaning that the remaining 90% are still lagging behind.
A major indicator of the industry's reluctance to digitize is its continued use of manual and/or cabled readings instead of wireless systems connected to digitized mining assets. Indeed, there remain a number of organizational barriers to innovative concepts like wireless readings, notably mining's status as a traditional, risk and change-averse industry, which prevents investment in potentially 'risky' technologies.
We are going to look at the ways that the most innovative mines are using new technologies to get ahead of the game, showing you that adopting these technologies could make your mining operations safer, more productive and more cost-efficient.
Autonomous mining vehicles have been around for nearly two decades now ' Rio Tinto's Pilbara iron mine introduced 80 driverless Komatsu trucks in , massively increasing their mining productivity. Many of the big mining players soon followed suit ' such as BHP Billiton and Suncor ' mainly buying from Caterpillar, Sandvik, Komatsu and Atlas Copco, who currently represent the most innovative and important players in the autonomous mining vehicles sector.
These vehicles revolutionized mining because, for the first time, they allowed humans to communicate with and control machinery remotely. This makes them ideal for use in underground mines as well as other hazardous environments where the human safety risk is high. Most autonomous mining machines are actually semi-autonomous rather than fully automated; in other words, they still need some human assistance for specific situations that they cannot handle on their own. These underground excavation vehicles are made autonomous through equipping them with remotely controlled tools and cameras, allowing users to perform actions and see the surrounding areas remotely. Nowadays, the focus has shifted away from the original autonomous mining vehicles towards building the 'autonomous mining system', which can carry out tasks automatically or with minimal external control, and also towards the possibility of full automation through robotic technologies.
Autonomous vehicles are revolutionizing mining by allowing humans to communicate with and control machinery remotely.
Able to operate below and above ground, autonomous vehicles are essential for the modern mine. They decrease incidents and increase workforce safety, work in mining zones that would be too dangerous for humans, increase mining productivity (as equipment can move faster and cover longer distances), and reduce costs as fewer operators are required to control machines.
Advances in wearable technologies make them an ideal tool for workforce-tracking in mines. They are especially useful for field maintenance and real-time machine inspection instructions, and improving operator-based care and safety ' especially for underground mines. These wearables allow for RFID personnel tracking and real-time visibility of all staff, allowing key workers to be located instantly. They can also be leveraged to identify where productivity can be increased, and to monitor staff time and attendance records.
Wearable technologies are an ideal tool for workforce-tracking in mines.
In terms of workforce safety, wearables and their role in a larger IoT-based monitoring network significantly improve response times in the event of an emergency, allowing both operators and staff to be immediately notified when an incident happens. They can also minimize safety problems ' and future accidents ' by restricting access to potentially dangerous areas in the mine. Workforce-tracking also allows for greater mining productivity, as workers are more effectively managed, and potential incidents that would reduce working hours are diminished, or even completely prevented.
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Global Positioning Satellite (GPS) positioning and navigation systems have recently been developed and implemented by some mining companies on blasthole drills and electric cable shovels in their open-pit mines. These GPS systems produce accurate, three-dimensional visualizations of the location of the drill bit or the shovel tracks in real-time via a Moving Map Display (MMD) on a screen. This allows the operator to accurately navigate the drill from blasthole to blasthole, maintain a desired shovel grade, or face position from a remote location. Durable, proven GPS components are needed for this type of system in order to withstand the often extreme environmental conditions. One example of the use of GPS systems in open-pit mines is by AQUILA Mining Systems Ltd., who have introduced GPS into their Canadian open pit coal and iron ore mines.
GPS enables operators to accurately navigate a drill from blasthole to blasthole from a remote location.
Mining operators have traditionally found it difficult to manage engineering and asset information throughout the asset lifecycle. Digital twins can help with this: they are virtual replicas of physical assets, processes, and systems, which provide a representation of both the core elements and the dynamics of IoT devices used within the space or system depicted. Digital twins use AI (artificial intelligence), machine-learning (a subset of artificial intelligence) and software analytics with data to render real-time (otherwise known as 'living') digital simulation models that are continually updated as their real, physical counterparts, or 'twins' change. To make it simpler: digital twins are like real-time 'video game' versions of mines, digitizing these spaces in a way that produces interaction between the real and the virtual.
Digital twins are virtual replicas of a mine's physical assets, processes and systems.
Digital twins allow mining operators to assess engineering data management capabilities and maturity in order to discover any areas where data or monitoring might be lacking, giving them the ability to channel their digitization efforts into the areas of greatest need and impact. Anglo American Plc, the UK-based miner of commodities such as nickel, coal and precious metals, for example, recently started using digital twins to optimize its mining fleet, including using applications to track the performance of haulage at its Los Bronces mining site in Chile, and at a 500-kilometer pipeline in Brazil.
In general, digital twin systems can be used to optimize the operation and maintenance of physical assets, systems and processes in real-time, massively improving mining productivity.
Operational Intelligence (OI) is key to creating digital twins of mines. OI is used when operators want to digitize parts of their operations in order to gather real-time insights and initiate data-based decision making in their organization. In mines, this translates into digitizing dynamic assets like workers, vehicles and critical assets (slopes, dams etc.) to visualize their behavior, aggregate this information and generate recommendations through the OI software, which are based on historical and real-time insights. These solutions learn from past actions through AI (specifically, machine learning) and can, therefore, improve their own decision-making processes.
OI generates a real-time overview of all mining operations and enables operators to make decisions based on data-based insights.
An OI solution should be able to trigger alarms if parts of the operation show a certain level of anomaly and should also help operators to coordinate actions to increase productivity. For example, OI can facilitate the real-time monitoring of all of the mine's many different assets to ensure efficiency and safety, or help teams to enhance the effectiveness of their communication methods, such as mobile apps and hand-held devices, in order to enhance productivity. OI solutions are able to ingest data from any data source and translate individual pieces of information into global, actionable insights.
It is estimated that most mines will digitize at least some parts of their operations with OI systems within the next 5 years. Moreover, within the next decade, the majority of mines are likely to begin working with a digital twin of their infrastructure and workflows. Today, however, most mines still have to take their first step toward virtual operations: replacing manual or automated cable readings with wireless monitoring systems.
With wireless monitoring mines can digitize assets and monitor their performance in real time.
Mining assets, such as dams, are usually in hard-to-access areas, meaning that manual readings by workers are both time-consuming and dangerous. When workers collect data and return to the office, the information they have gathered is already outdated: working with non-real-time information can have a critical impact on mining operations. Pore water pressure in tailings dams, for example, can change quickly, putting pressure on the infrastructure that can cause dam breakages, often with highly damaging effect. With cabled readings, operators can diminish risks by automating data gathering processes. Installing cables throughout a mine's infrastructure, however, can be costly and, depending on the area, complicated and time-consuming.
A third option comes in the form of wireless monitoring systems that can connect a variety of sensors, such as piezometers for pore-water pressure measurements in tailings dams. They transmit real-time data to a gateway and can transfer information to a server based in a control tower up to 9 miles (15 km) away, allowing operators to remotely monitor critical assets. This generates greater productivity as asset availability remains almost constant.
To summarize ' with wireless monitoring systems operational costs are lowered not only because mining companies no longer need to send a human being to read the data ' thus saving money on hiring staff, and on vehicle and petrol costs ' but also because there is no need for expensive cabling and maintenance operations. As critical assets are better maintained, this in turn increases return on investment.
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