Rio Tinto found itself in a position where all of its data collections, at one point, were islands of information that were neither talking to each other nor linked.
"We had exactly the same system as any other modern mining company has today," Rio Tinto head of innovation John McGagh said.
It wasn't until the company began treating data as an asset in 2007 that the multinational mining company took the initiative to kick start what would be a seven-year program that would see all of its data sets from its fixed and mobile assets linked, and remain location independent.
"We started our program basically when we said, 'It would be very nice if we could wire together all of our information systems and get a complete picture of our mobile assets'," he said.
"So we [took advantage of the Internet of Things] before we knew we were going to do it."
According to McGagh, the initial part of the program was to ensure its 14 operations in Pilbara, Western Australia, could be controlled from 1,800 kilometres away in Perth, "simply by pushing a button and seeing machines run".
The company decided to tackle the challenge head on by starting with the most difficult task first: Connecting all of its mobile fleets around the world.
In Pilbara alone, Rio Tinto has 900 automated truck fleets that typically run on electric drive systems and have been programmed to drive themselves. Each uses GPS and radar-guidance systems to accurately drive along predefined pathways within the mines. The automated trucks are also installed with 300 to 400 sensors, and produce approximately 4.9 terabytes of data each day.
McGagh said that while linking its mobile assets may have been the most difficult task, it was also the most important.
"Mobile is at the front of our production process," he said. "Mobile is where we touch the ore bodies, and the ore bodies are the source of our wealth."Mobile assets are the true Internet of Things, so wiring together and getting connectivity between mobile assets that move is a lot harder than wiring together and getting connectivity for things that don't move."
Following the connection of its mobile assets, Rio Tinto moved into connecting its fixed assets, including its concentrators, which are located in a number of its facilities in Australia as well as in the company's sister plant in Mongolia. McGagh said that each concentrator is approximately the size of a large city block, and pumps out data using the 60,000 sensors that are installed at each location.
"The concentrators are processing what we've already dug out with our mobile fleet. So we wanted to go where the largest source of the wealth was, but we knew it was hard, we knew it was very hard, because in a mine, there are no fixed sensors, because we change the shape of the mine every day because we dig it. The sensors are actually the mobile fleet," he said.
"A truck has about 300 or 400 sensors on it; it knows a lot about its world around it and the geography. If we're going to build the value chain, we think we can get to the fixed assets relatively 'simply', but it's no use just getting to the fixed assets unless you can get to the upstream assets that are feeding that."
To complement the data that the company was gathering in the field, Rio Tinto launched the processing excellence centre (PEC) in Brisbane, Australia, last year. It examines and processes real-time data from seven of the company's mine sites in Mongolia, the United States, and Australia in order to ensure that it is able to maximise productivity and improve performance.
Prior to the launch of the PEC, Rio Tinto ran trials of the program and found that through the PEC, adjustments to the company's flotation process resulted in an increase in the recovery of copper and gold at Oyu Tolgoi in Mongolia.
"[It was] really in 2011, 2012, we started with fixed, and started to turn that into a platform where we started to add value to the business," McGagh said.
However, the project wasn't always smooth sailing. The main problem the company faced was trying to make sense of all the data that was collected. At one point, McGagh said he had a moment of, "How the hell are we going to get information out of this?"
McGagh discovered that the trick was to overlay the information on an advanced interface that replicated a gaming engine.
"To make sense of the data, you have to unlock it, and we do a lot of translation of the raw data coming in, and that paints us pictures, so it's like going through Sim City -- but it's real. How do you make sense of very ambiguous information, and once you've done that you can go in there and play with it," he said.
"A human would struggle to read if they had to try translating it. The overlay is a systems interface, and is a really powerful gaming engine."
As for what infrastructure was required to support the influx of data, McGagh said Rio Tinto used its existing intranet, which houses the company's ERP and server systems, to support the process.
"Working with our ICT colleagues, we were able to find a route where we could manage the data without bringing the system down, and it worked. It's one of the advantages of being big, actually," he said.
Since introducing interconnectivity to the business, Rio Tinto is now able to oversee the operations of its assets.
"We can now see our physical assets in all of our pits. By the end of this year, we'll have about 85 percent of our mobile fleets deployed, and that allows us to have a parallel view of the data we collect, which will let us understand where the trucks are in our geography," he said.
"We're pulling vital data so we can understand what they're doing to our geology."
When asked how much Rio Tinto had invested in the project, McGagh said it was a "substantial, but not eye-watering" amount, and that the return on investment would be worth it. In fact, McGagh said that after three to six months of the project, the company was already generating AU$18 million in cash flow.
Going forward, Rio Tinto expects the data collected from the field, which McGagh refers to as "real-time, fast data", to be combined with its ERP system, which produces "near real-time, slow-moving data", to take advantage of predictive analytics.
"So I think what we've done is we've generated value from these systems, and we're going to generate a lot more value out of these systems, as it'll tell us what's happening in the now, as we take action in the now. As we build up the rich data sources, we'll be able to project forward and use predictive analytics to predict the future," he said.