When IoT Meets Mining

When IoT Meets Mining

Mining is on the edge of the succeeding industrial revolution, driven majorly by data technologies being developed for consumers, and this point, it'll be available to mines of any size. Some might agree the “modern” age of computer-driven technology in mines began within the 1980s with computer-based dispatch and machine health alarms. The concentrator plants came up alongside other process-based dealings including SCADA, and subsequently historians and expert systems, alongside other process-based technologies. Large volumes of knowledge and therefore the data science to process that data has existed for an extended time but had not garnered much attention, until now.

During the super-cycle, large mines invested during a generation and elegance of technology that had been proven over the last decade previously. Dispatch systems, to advance truck, movements to shovels, and operator aids, like a drill analyzing system to assist the operators, also generated important volumes of information through onboard computers. Large in size, yet low-volume in manufacturing, custom-designed hardened computers, touch screens, external GPS, were installed within the mobile equipment, the info sent over expensive in-pit Wi-Fi systems, landing in organized databases in an office server, and whose key output was nominal reports. The business model was to form high margins on the hardware and recurring revenue from a typical support package. These systems have, and still, produce information like machine health, drilling records, mobile Fleet Management Systems (FMS) production analyzing, and time-series data. CIOs are very successful at deploying these technologies and supporting the reporting tools. However, my data remains highly underutilized, as most mine managers and engineers would attest. Few companies even monitor the info utilization. like all asset that's the results of the investment, it must have high utilization so as to maximize the return on investment. the primary step to maximizing the worth of knowledge is to watch its use and make someone quantitatively accountable.

Due to the value, complexity in deployment, use, and support, only the most important mines are ready to afford the current-gen technologies for mobile fleet management. Therefore small and medium-sized coal mines, nearly all cluster and cement (limestone) mines, most medium and smaller underground mines, civil earth-moving attributes, and industrial mineral sites cannot provide current-gen mobile equipment monitoring and optimization technologies.

"Any CIO seriously contemplating engaging in big data efforts, beyond one-off projects, should be prepared to make an integrated contextualized integrated data infrastructure"

These mines typically have far fewer data since much of it's collected on paper then transferred to a spread of custom spreadsheets and databases. New reliable technology can change this.

The past five years have seen a change in our personal lives from mobile devices (tablets and smartphones) and data. we will all use the cloud to store information, where complex data are often processed and fed back to us quickly and in engaging ways.

The apps are often highly addictive, as they're designed to be, thanks to frequent feedback and elements of social interaction. With these devices, we will know our outdoor position anytime, and that we have a spread of ever lower-cost wireless communication channels to attach to the online. Our apps still function, albeit with some limitations, even when not connected. Small low-cost simple equipment, that uses our phones and tablets as interfaces and communications bridges still enrich our museum, shopping and fitness experiences. Why not in mines?

Even the primary technology-imbued operations and nearly all other operations still collect most safety information on paper, deleting the power to simply track and analyze trends and notice patterns. Operators can expend entire shift rotations without ever receiving a response, negative or positive, about their performance. Supervisors at the most mines spend an hour before and after the shift finishes, doing paperwork, entering data into a spread of systems, and even during the shift, are expected to drive around the pit to urge a visible perspective of how the mine is performing. This low-feedback, paper-work intensive work has remained unchanged for many years. Operators can obtain feedback on their own activity which of their team, through appealing user experiences, almost like how multiplayer online games present highly engaging feedback at the top of each match, during this case, shift. Supervisors would even have a far clearer perspective and may even spend time within the pit when and where it counts because all the info is at their fingertips. However, the absolute volume of knowledge that these sensor platforms can generate is astonishing. 

The Big Data revolution, that's transforming other businesses, is predicated on the high volumes of knowledge drawn from web, sensor, and other data sources, that are mostly within the sort of unstructured data. aside from data collected from next-gen mining apps and IoT, most data in mining is that the more common structured (SQL) data and time-series data. These sets of information might be still organized using more traditional techniques, but executive pressure to hitch the “Big Data” bandwagon will undoubtedly force CIOs to test the technology’s relevance to their own operations.

Processing the info through complex algorithms is really the smallest amount of time-consuming step in an analytics project. the foremost time-consuming step is that the data preparation phase, where data, typically from disparate sources are integrated into a standard contextual model using domain expertise. Far and away the foremost challenging step during a big data project is to rework workflow, in other words, to realize action from data.

The most immediate transformation in mining within the next few years are going to be the introduction of tablet apps and IoT as data collection and control systems, mostly at small and medium-sized mines. Because the current generation of fleet management systems that were recently purchased reach the top of their life cycle. 

Although mobile fleet automation undoubtedly gets the foremost interest, the extent of control, cost, isolation, inflexibility, and complexity will prohibit its use to only the very largest and most sophisticated mines.

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