Mining Geophysics News, Regular Columns, Vol 25.4

Mining Geophysics News

Moe Momayez

moe.momayez@arizona.edu

In this issue of Mining Geophysics News, we look at the latest technologies that have brought a step changes in the mining industry. Autonomous haul trucks and robots, augmented- reality simulators used for training, real-time data analysis, and self-flying underground drones are precursors of yet more changes to come. In this edition of Mining Geophysics News, we are pleased to present an article written by Debra McCown, first appeared in the September issue of Mining People Magazine (Vol. 42, No. 6), which is reproduced with the express permission of MPM.

EEGS welcomes contributions of mine site and mining geophysics news and articles from mining engineers, geophysicists, geologists, hydrogeologists, geotechnical engineers and environmental scientists in local and international firms, research, academia, service providers and government agencies on topics that may be of interest to both the mining geophysics practitioner and end-user communities. Please contact me, Moe Momayez (moe.momayez@arizona.edu), Associate Editor, with your ideas, news, or articles that you would like to share with us.

The 21st Century: A New Era for Mining Tech

by Debra McCown

So, there’s a global pandemic, and you have to work from home. That’s fine. You’re an equipment operator, so you don’t have to go to the mine anyway. You can do like you always do: Log in from a comfy chair with your virtual reality headset and drive a piece of equipment that’s located on the other side of the continent.

It’s kind of like a video game; in a way, you’ve been training  for this kind of job your whole life. You aren’t exposed to any dangers – and the only real risk of germs is from the leftover pizza you forgot to put away in the fridge last night and are thinking about eating anyway.

Don’t eat it; that’s a bad plan. A drone can be at your door with something fresh in like 20 minutes.

So, maybe we’re not quite there yet. If you hate your commute, you’re still stuck with it if you work in a hands-on job. And if you love the rollercoaster of emotion that comes with working in day-to-day operations, you can still be present to experience the collective satisfaction that comes with a job well done. But

with the technologies that are now coming into play, all of that could change. From real-life robots to virtual-reality modeling and real-time data analysis to round-the-clock autonomous fleets of haul trucks, software-based technology is changing the face of mining – and it will totally shift the way things are done in the future. We’ve all heard a lot in the last few years about new, data- and computer-based technologies that are having an impact in the mining industry. And it’s a lot of information! There’s been such an explosion of new tech in so many areas all at the same time, it can be a challenge to wrap your mind around it all.

So, where do you start? How do you determine which new technologies might stick and be relevant to you and which are just distracting shiny objects? Most of those questions can’t  be answered in the pages of a magazine. But what we can do is provide an overview – a lay of the land – of the major tech trends that have emerged.

Right now, there are so many different things happening in technology with so many moving parts, there are countless ways to organize and categorize them. And while there’s no one right way to do so, we hope the way we’ve done it here  will help you wrap your mind around the current technological landscape as it relates to mining.

In the end, it all comes down to data – and the ability to use that data through digital connectedness, computer analysis, and application to real-world processes and equipment – that is driving the new technological approach that some have dubbed “the mine of the future.”

One way to look at the technologies is to think of them in three categories:

  1. Data You Can See: This area has to do with the way we humans interact with process data visually to accomplish a task or make decisions. It includes things like 3D modeling and mapping, virtual reality training simulators, and augmented reality overlays of information. These technologies translate data contained in computers into a format that humans can visualize and interact with.
  2. Data Only Machines Can Process: This area has to do with the collection and analysis of minute pieces of  information in large volume. It includes things like information gathered by a scanner to calculate a pile size or aid in exploration,  the reduction of downtime through predictive maintenance schedules designed based on data generated by sensors on equipment, and the kind of real-time digital connectivity that makes it possible to operate equipment remotely.
  3. Data-Driven Equipment: This area includes the hardware that interacts with the physical environment. It includes things like drones with various functions, autonomous equipment, and robots or robotic tools being used to perform tasks. Because these technologies are more concrete, they tend to get more attention – but none of them would work without a software foundation. Here’s an overview of some of the technologies and trends in each area.
Figure 1. Simulators that, in video-game fashion, put you in the shoes of an equipment operator.
Figure 2. The environment is visible on screens at this Komatsu facility.

Data You Can See

They’ve become a common attraction at trade shows in the last few years: simulators that, in video-game fashion, put you in the shoes of an equipment operator. The simple ones are an arcade-

style setup with a seat facing a screen. Others are totally immersive, with the environment visible on screens that surround you.

Sometimes companies show these off to the press, too, showcasing them as their latest piece of technological gadgetry deployed in the name of safety. They have a very practical application: These machines make it possible to train people for the conditions they’ll face on the job without the time and risks of getting in the cab of a piece of equipment before they have hands-on experience.

One thing that trainers tout as a plus: their video game-like quality, which makes them a highly familiar medium to younger generations, which have grown up playing games with similar graphics. In the future, some say –as remote operation of equipment becomes more common and companies seek to mine in increasingly challenging environments – the simulation may end up being a lot like doing the actual job.

The ability to show an immersive virtual reality visual also has some other applications. For example, as a tool to give potential job applicants – such as students in high school, trade school, or college engineering programs – a realistic view of what mining is like, with hopes that they’ll consider it as a career field. Or as a public relations tool to give lawmakers and media influencers an updated understanding of an industry that, to some, is still pictured with antiquated picks and shovels – and do this without the need to first convince them to travel to a remote site.

But training simulations and interface with the public are just two simple examples of the many ways that data can be turned into visible form. A host of data visualization tools are now becoming more commonplace in industries like mining and construction, which can use them to visualize how they will change the physical environment.

Three-dimensional modeling – for example, geologic modeling that can process large amounts of current and historic data to create a fairly accurate idea of what’s below the surface – is    a great help in exploration and, ultimately, mine development.

Somewhere in between the concepts of computer modeling and complete virtual reality is augmented reality: a technology that enables people to view models and other data visually in areal-life environment.

For example, it’s possible to literally see a future construction project on your job site, says James Benham, CEO of JBKnowledge, a Texas-based technology solutions firm which serves the construction industry.”

HoloLens is a game changer. It gives you the ability, using the right software of course, to take our 3D models of your job site and render them as a hologram, walk around in them, re-size them, move them around and manipulate them, and have a meeting with others about it,” Benham says. “You can see  it  in a field of grass. It’s amazing.”

Benham has a pretty good understanding of what it takes for technologies like this to be developed: the vast majority of his team of 230 spend their time writing code – and they also rely on a lot of existing code to get their work done efficiently. Their reality is a

lot like the tech trend as a whole: It took generations to get here.”

Why is all of this coming on the market now, and what forces have conspired and combined with each other to lead us to what you see now, which is really a proliferation of automation technologies?” Benham says. “All of these technologies have been independently maturing, and they are being combined in ways that takes it from zero to 100 miles an hour in the blink of an eye. It’s pretty stunning.”

The proliferation of autonomous technologies, he says, depended on first having their component parts: things like local computing, cloud computing, high-speed network connectivity, high-quality cameras and lasers, photogrammetry, good GPS data, machine learning, sensors, really good software apps, low-cost storage, and the ability to process data on a handheld tablet.

Their adoption in the workplace also depended on the normalization of tech trends through consumer expectations

–and the development of lost-cost components that make them practical to use on the job. In today’s fast-developing world, he says, the use of tech tools is becoming more essential.

“You’re looking for a way to multiply your workforce by making them more efficient and more effective, and this is one of the main ways of doing it,” Benham says. “It’s not about replacing workers; it’s about making the skilled workers you do have far more effective so you can keep up with demand.”

Data Only Machines Can Process

Before drone-mounted scanners came along, trying to measure anything on a site – from a pile of material to characteristics of an area being considered for exploration – was a time- consuming, labor-intensive process.

Even with GPS and computers, it would take all day to gather a handful of data points and calculate needed information using a computer. Aerial imagery created from an airplane, meanwhile, would cost a small fortune – and with months of lag time to  get the images. It simply was not possible to gather the kind   of data that’s now accessible via technology.

“Historically we’d go out with a GPS and walk around with a GPS stick taking points, and we would take those points, and we’d come back into the office and create a 3-D model,” said John Blackmore, mapping and survey supervisor at a quarry in Virginia, in an interview two and a half years ago about how the introduction of a hobbyist drone had begun to change things.

“In a 6-hour workday on site, we might be able to collect 200points to make that 3-D surface. With a drone, we can get millions of points in half an hour,” he said. “So, it’s much better data, it’s more precise, and we’re taking a person out of the field.”

In the time since that interview, a hopeful idea he shared –an automated drone that would fly itself daily to collect data and automatically send it to a computer for processing – has become a commercially available product. Now, machines can gather and process these massive amounts of data completely on their own.

It’s hard to have a conversation about exploration these days

without somebody mentioning data-gathering drones, which make it possible to collect information about areas that are difficult for humans to access. But drone-mounted cameras and scanners are just one example of how the explosion in data-gathering – and the computing power to process it – is changing the way things are done in mining.

Another technology that’s gotten a lot of attention lately is the “internet of things,” a term that refers to the interconnectedness of everyday objects embedded with computing devices, which enable them to send and receive data.

In a mining context, this means all kinds of equipment can be monitored by a computer, and the data can be collected to generate things like predictive maintenance schedules, which make it possible to avoid downtime by doing maintenance before breakdowns occur.

Meanwhile, sensors of all kinds can be monitored to collect a feed of data in volumes too large for a human to reasonably digest but easy for a computer to process into useful information. And the cost has come down so much, even a relatively small work site can employ this technology to monitor various conditions at the mine.

This digital connectivity and ability for  constant feedback is, of course, also necessary for other technologies, such as the remote or automated operation of equipment.

While “big data” might get a bad rap in the consumer space for its ability to accumulate personal information, in the case  of industry it means the ability to identify patterns and trends  in real time and answer business questions in a way that aids in decision-making, from mineral exploration to production to regulatory compliance to tailings management.

The ability to gather and process technology on an unprecedented scale means that, in the 21st century, the data-driven approach is here to stay.

Figure 3. Cargo drone.

Data-Driven Equipment

The terminology that’s thrown around with autonomous equipment can be a little touchy. Even Built Robotics, whose marketing tagline advertises “robots that build the world,” tries to use less evocative terms in explaining its products, says Erol Ahmed, communications director for the company, whose software enables ordinary hydraulic equipment to operate autonomously.

The word “robot,” he says, brings to mind different things for different people – from Hollywood’s malevolent sci-fi movie killers to benign but inaccurate impressions of robots as human-like machines that can do a multitude of tasks.

In reality, Ahmed says, robots are much more limited tools, and their design is based not on creating some do-everything gadget, but on accomplishing specific goals. The tasks they’re designed around generally fall into three categories: safety, remote work, and mundane tasks that can be easily automated.

“They’re tools like any other,” Ahmed says. “You could dig a hole in the ground with a pickaxe and a shovel and a wheelbarrow

–which, by the way, were major inventions back when they were invented – then you introduced steam power and hydraulics into construction equipment, and that was a huge shift. And now, instead of a person who digs holes, you are now an operator.”

Just as the advent of  hydraulic equipment made it  possible  to build skyscrapers, bridges, and dams, he says, automated equipment is simply a tool to get more work done safer and faster. Both machine learning – a computer’s ability to improve from experience – and artificial intelligence – its ability to make decisions based on that information – have come a long way.

The kind of software-based technology that makes autonomous equipment possible has found its way into every kind of equipment. Big equipment manufacturers like Caterpillar and Komatsu are among those on the leading edge of making it available in mining.

Caterpillar, for example, offers autonomous or semi-autonomous options for several types of equipment: mining trucks, blasthole drills, dozers, underground loaders, and longwall systems. According to the company, the most commonly used autonomous mining technology right now is the haul trucks; hundreds are now in operation around the world.

Figure 4. CAT command for dozing, semi-autonomous systems, operator station.

A fully autonomous piece of equipment is able to work without human intervention other than fueling and maintenance, while a semi-autonomous piece of equipment is able to do most of its work without human intervention. For example, a semi-autonomous drill might be able to complete a row of holes on its own, but then must be moved by an operator with a tablet for the next row; a fully autonomous drill could complete multiple rows on its own.

“The push toward autonomous mining doesn’t show any signs of slowing,” said Sean McGinnis, Cat MineStar Solutions product manager, in a recent news release. “We have projects in the works with a number of large mining companies either looking to expand their current autonomous haulage operations or implement new ones.”

Built Robotics, meanwhile, is scaling the autonomous concept to smaller companies that maybe can’t afford to buy brand new equipment but can afford to pay for hours on the software to accomplish tasks through automation.

Another frontier being explored is the potential to develop self- charging vehicles, which would eliminate the need to refuel.

Meanwhile, drones are being looked at fora host of new uses. Beyond performing site inspections, they’re also being looked at as a means of transporting people and cargo – particularly in remote areas of the developing world, where traditional forms of transportation are often lacking.

Assen Aeronautics, for example, has been showcasing a drone that resembles a flying space-age motorcycle and is designed

to carry 200 pounds up to 50miles. While U.S. regulations require a human pilot, in a lot of other countries it could operate autonomously, which could be a game-changer for delivery or parts and other urgent needs to geographically remote mine sites.

The technology has also been looked at for some seemingly low-tech applications like herding livestock.

Ahmed says the proliferation of technologies based on data, software, and computing will undoubtedly continue to grow, leading to the “upgrading” of human jobs as increasingly sophisticated software enables machines to take on more menial tasks, freeing up human labor for other things. But the revolution in technology won’t stop there; work will be re- thought and re-designed, and processes will be changed to remove unnecessary redundancies leftover from the era before autonomous machines.

The changes that are to come in future years, he says, will undoubtedly go beyond what is currently envisioned, as technologies are combined in not-yet-predicted ways and result in yet-unknown impacts.

“Henry Ford helped launch the car revolution, but he couldn’t imagine the building of the highway system and that people would have drive-in movie theaters, and the whole culture of the suburban exodus,” he says. “The major shift in the 20th century was about what you can manufacture. I think the 21stcentury will be more about the technology you can create. So, I think we are shifting more into a software-focused world.”