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  • Mining and Energy

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    Tim Kannegieter


    The mining and energy (oil and gas) industries cover a complex web of operators and suppliers which must work together to deliver commercial outcomes. Drilling platforms and major mines have been early adopters of control technologies, being highly sensored - albeit connected primarily via wired systems.

    Early efforts focused on major productivity improvements, such as having communication links transmitting the data to a headquarters, allowing a higher percentage of the workforce to work from cities rather than on site. However, periodic downturns in the industry require ever increasing efficiency improvements and IoT has the potential to deliver on that through smaller incremental improvements. Coupled with the global factors driving the IoT revolution, mining and energy are industries ripe for the application of IoT. 

    Because Australia is a world leader in these sectors, it is considered there is an opportunity to also lead the world in the application of certain areas of IoT e.g. data analytics for mining.

    Application areas

    The major areas of opportunity for IoT in mining and energy are monitoring and optimization, safety systems, geological systems, site-wide operating systems, and automation.

    • Monitoring and optimization covers condition monitoring of mobile equipment and fixed plants. It covers communication systems, platforms for condition monitoring, data re-purposing and predictive analytics resides.
    • Safety systems include connected wearable technologies, monitoring employees in real time with personnel tracking with location mapping, even seeing what they can see,
    • Site-wide operating systems include automated equipment (such as drill rigs, trucks and lab robots),  automated plant operating autonomously to optimise operations, condition monitoring, site surveillance. Site wide system involved integration of a wide range of platforms as no one provider in the ecosystem has the entire holistic solution. In fact the industry is characterised by many providers with solutions specific to parts of the ecosystem. Interoperability and data re-purposings is critical to optimal operation of the ecosystem. 
    • Geological sensing is well established in oil and gas, and increasingly applied in mining. It’s taking geological measurements from the rock during real-time operations, working with the data, transmitting it to surface and back to headquarters for interpretation. Data specifically about the same rock comes from different measurements at different times in the project, e.g.e including gravity and magnetic geophysics work done up front, potentially some magnetotellurics a few months later and then actual drilling data. The resolution of the site view is developed and interpreted over time. There is a huge volume of data (the average seismic exploration generates petabytes of data) and analytical/visualisation techniques being matured in IoT systems will play a role to advance this field. 
    • Environmental systems for monitoring changes to the environment. Some mines are starting to use drones  to replace traditional environmental surveying techniques. Drones can collect lot of visual information within a short space of time and have it analysed by advanced cloud based systems. This can be used to monitor wildlife and  flora. Most mines have an over-arching environmental plan to rehabilitate the land as it originally was so you don’t want any introduced species of flora being introduced so you need to monitor population and target areas to ensure you're managing the environment properly. Environmental systems are also employed in a range of associated operations such as dredging and stockpile management, with dust sensors, temperature sensors, water flow sensors, pulling all the data into simple display and management system. Increasingly this kind of data is being displayed on live Web feeds, so the general public can see what’s going on with their environment, what the impact of operations are on the local environment.

    Specific technologies of interest in mining and energy include:

    • Sensors: Advances in sensing technology will be a driver of efficiencies. For example, sensing technologies are being developed that can be placed directly behind a drill bit to analyse rock in real time rather than waiting for lab tests. Another area of opportunity lies in stockpile management, where better sensing of ore grades will help decide what to put through the mill and when to process it.
    • Drones: Because of the geographically dispersed nature of mining and engergy industries, operators are investing heavily in drones. A drone and single pilot can complete the same work loads of an eight-man environmental study team. Challenges include battery life versus weight and line of sight regulations, which restricts what operations can be done around areas such as railway line inspections etc. There is also a problem with raptors attacking drones which they view as prey.
    • Autonomous vehicles: The mining industry was an early adopter of autonomous vehicles. There is, approximately, a worldwide population of 100,000 mining trucks, compared to over a billion road vehicles. With automotive companies in a global race to introduce self driving cars, the mainstream technology will quickly surpass the early mining technology. For example, suspension technology that adapts to potholes and inconsistencies in the roads would be very useful on mining trucks, which typically costs around half a million dollars every time a tire blows.

    Key issues

    • Interoperability: Because there are so many niche suppliers in mining and energy, there is a challenge around interoperability between platforms and systems. There is an argument that these industries should leverage standards developed in other industries, such as Industrie 4.0 (See manufacturing). An aspect of this is the need for modularity in the development of software systems. Such systems are developing so fast that it hard to predict what the final deliverable will be. Modularity in systems allows flexibility.
    •  Repurposing of data: A large percentage of data collected in mining and energy is not used. However, if that data is accessible to other systems, there is potential for suppliers to come up with new idea of how to utilize that data - to squeeze more value from it.
    • Cultural bias: The mining and energy sectors have traditionally been very insular, with an attitude of going it alone with development of technologies. However, with the rapid pace of development in IoT, this culture means the industry may not take advantage of the latest technologies and begin to lag behind in productivity. 



    • IoT MER: The Internet of Things Cluster for Mining and Energy Resources. 


    The information on this page was primarily sourced from the following:

    Edited by Tim Kannegieter


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