5 Lessons From Advanced Mining IoT

by:
on December 12, 2016

Industries that rely on machinery, such as manufacturing, utility providers and oil and gas companies, are increasingly using the internet of things (IoT) to further optimize equipment maintenance and reduce costs.

You could say IoT is now mainstream—Gartner estimates that more than half (56 percent) of asset-intensive industries will have added IoT strategies by the end of 2016. (The full report, “Your IoT Future Is Visible in the Mining Industry Today” by Bruce Robertson and Kristian Steenstrup, is available to Gartner clients.)

Mining IoT, in particular, offers several advanced use cases that can serve as a templates for other industries to follow.

In this piece, we’ll share five ways the mining industry has utilized IoT capabilities and established best practices, and what other businesses can learn from that example.

What Is the Internet of Things Anyway?

The term “internet of things” implies more complexity than is really there.

In the most basic sense, the IoT is the concept of attaching sensors or controls to normally inert objects so they can connect to the internet and communicate with other connected “things.”

So really, there are three basic parts to IoT technology:

Below, we dive into ways the mining companies have implemented this technology, and how it can be used in many other industries.

1. Use Sensors to Move Toward Proactive Maintenance

One of the simplest, and most impactful, uses of sensors and IoT technology is moving beyond reactive maintenance. Many mining IoT maintenance strategies have advanced past waiting for a breakdown before taking action.

Perhaps you’re a maintenance manager in manufacturing or oil and gas; there’s a good chance you’re already using an enterprise asset management system (EAM) to address machine breakdowns with maintenance scheduling based on a calendar.

Scheduling calendar-based maintenance in TabWare by AssetPoint
 

To move beyond this type of predictive maintenance, you’ll need sensors attached to assets, feeding real-time condition data into the EAM or maintenance management system (CMMS).

Users can then set up thresholds for each asset, and when the condition data falls outside that range, the system can automatically dispatch a technician to address the problem before it actually occurs.

And here’s where asset performance management (APM) comes into play: Where a CMMS and EAM focus on maximizing the useful life span of equipment, an APM system steps in to manage the performance.

Differences Among CMMS, EAM, APM

The APM can gather gigabytes of asset performance data each day to be analyzed. Once a trend is identified, the EAM can automatically adjust maintenance schedules to prevent a costly breakdown, which “closes the loop” by translating raw data into a corrective action.

This process of attaching sensors and streaming data is becoming more affordable, so companies can easily monitor the condition and performance of less expensive assets.

Among advanced IoT users such as those in mining, this strategy is commonplace. But using sensors can be a useful entry point for smaller businesses trying to achieve more proactive maintenance standards.

2. Carry IoT Capabilities Into Other Areas

Mining IoT implementations began in the maintenance and reliability realm, and many mining organizations say they’ve optimized maintenance costs so much that there’s little left to improve in that department.

Just like them, other industries should think about IoT benefits outside the maintenance box. Here are a couple examples:

  • Some mining companies have enabled remote control of certain heavy equipment by combining the operational technology that physically controls machines with IoT systems. This delivers benefits such as increased safety for operators and enhanced performance.
  • Secondarily, the IoT can help companies identify the root cause of a performance issue, even if it originates in another asset or department. If a conveyor belt slows down, technicians are likely to only make adjustments at the belt. With IoT sensors connecting systems and assets across business silos, the techs will know if the slow conveyor is actually due to a seemingly unrelated problem in another department.
Case Study: Australian Miners Free Up Trucks to Boost Revenue
Fortescue Metals Group transformed data gathered from its fleet of large mining trucks stored in an EAM system to give managers a mobile view of how much ore a truck is carrying, and whether that truck is full.

For the first time, this capability allowed managers to radio drivers immediately if their truck wasn’t full to instruct them to maximize capacity. Because of this, some trucks were able to help out at other mines at no additional cost.

The result was increased capacity of trucks and the increased yield of valuable ore, both of which led to a significant revenue boost.

3. Enable Real-Time Analysis

Traditionally, analytics that alert users when a motor needs to be repaired aren’t performed as the data rolls in. By switching to real-time analytics, organizations can achieve operational awareness as the data is being collected.

The analysis can be performed in multiple ways: either by human workers making decisions as the data is gathered and displayed in an EAM, or by user-defined actions that can be triggered as data comes in. In some cases, even more advanced intelligent analytics can be used.

A visualization of real-time power usage data in Fluke Connect Condition Monitoring
 

Of course, real-time analysis is useful for more than determining maintenance tasks. Mining users offer a good example.

Case Study: Goldcorp Improves Safety With Real-Time Employee Tracking
Mining corporation Goldcorp drew attention with its “connected mine,” where all employee helmets were fitted with tracking devices to monitor their locations in real-time.

The most obvious benefit is safety, as managers can ensure every worker is accounted for and that they’re not entering prohibited areas of the mine. But Goldcorp decided to extend the real-time IoT strategy to other areas.

In order to keep a supply of fresh air in the mine, the company developed a system called Ventilation-On-Demand, which improved air flow, energy use and production, and reduced operational costs because airflow could be supplied only when and where it is needed.

This is a good example of both using real-time data analysis and using IoT strategies in multiple departments.

4. Consider Increased Autonomy and Smart Machines

Remote control of machinery or vehicles has delivered safety and production boosts in mining. Another use of IoT-related technology and real-time data analysis is autonomous smart machines.

By using sensors and controls on assets so that they can communicate with other assets, companies can program them to perform simple tasks or make more advanced decisions based on current conditions in a mine, refinery or factory floor.

This may seem too futuristic for smaller or midsize companies to feasibly implement, but the hardware is increasingly affordable.

Even a small manufacturer, for example, will have several expensive assets; if these companies start automating the more pricey machines that perform hazardous, repetitive tasks, it can deliver cost savings in labor and maintenance, as well as more consistent production.

A Sawyer robot programmed to perform tasks on a manufacturing line.
(Source: Rethinkrobotics.com)


Case Study: Rio Tinto Automates Smart Trucks for Safe Hauling
One of the world’s largest mining corporations, Rio Tinto, is in the process of automating many of its vehicles and machines throughout the Pilbara region of West Australia.

They call it the “Mine of the Future,” with 69 driverless trucks controlled by autonomous haulage systems to haul ore from the mine to the processing plants more efficiently and safely than human drivers. The company plans to expand automation to trains and diggers.

The company’s operations center in Perth houses controls for all autonomous machines at every mining site in Pilbara, which gives the company a comprehensive view of operations with visualizations and dashboards and the ability to collaborate among mining teams, all in real-time.

This helps managers to optimize logistics and maintenance of every mine from a central location.

5. Plan for a Machine-Only Future

Finally, nearly every industry foresees more people-less operations. Mining companies still require many employees on-site for now, but they’re heading toward a machine-only future.

Manufacturing is one industry where machines are filling roles formerly occupied by humans; Industrial robot sales in 2015 were the highest recorded in a single year.

However, any business with remote or dangerous work sites can benefit from removing living employees from the location and replacing them with robots that can perform longer without a risk to human life.

Moving to machine-only processes will take time, but companies of any size can prepare for this future by identifying tasks that make sense for full automation and developing a long-term plan to implement the technology when the business value will be most impactful.

Recap and Further Reading

Let’s recap the five IoT tips from mining:

  1. Use sensors on machines to stream condition data so teams can plan more efficient maintenance tasks before costly problems occur.
    1. Consider how IoT technology could benefit other areas of the business, or how it could reveal root causes of problems with assets.
      1. Enable real-time analytics to tackle issues immediately and gain a holistic view of operations.
        1. Identify business processes that could be made more efficient by autonomy and smart machines that can communicate with each other.
          1. Make a plan to reduce employee exposure to dangerous or repetitive tasks by introducing robotics.

          So what does all this mean for smaller companies? Think less about your size, and more about the cost of your most important assets and the risk involved in the tasks your employees perform. Any asset-heavy business can benefit from using IoT technology on critical assets for enhanced condition monitoring and performance.

          To learn more:

          • Check out our top CMMS and EAM vendors. These systems are commonly used in coordination with IoT and smart machines to achieve optimal maintenance and performance.

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