Go Big on IoT Value with Preventive Maintenance

By combining connected sensors, analytics, and machine learning, preventive maintenance brings together the elements you need to maximize IoT value.

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Go Big on IoT Value with Preventive Maintenance

This series describes four fast paths to an assured payback on your Internet of Things (IoT) investment. We began with How to Get Started with IoT, and have so far discussed the first three fast paths to value: Connected Operations, Remote Operations, and Predictive Analytics.

In this final installment, we’ll look at the fourth proven fast path to value, Preventive Maintenance, where you not only predict potential issues but can also prevent them from happening.

Big Mines, Big Trucks, Big Problems

Imagine you’re standing in a sprawling open pit mine. It’s in the middle of nowhere, two miles across, one mile deep, and specked with 45 gigantic autonomous trucks hauling iron ore out of the pit. Each wheel on those trucks towers over a person standing on the ground, and each pair of tires costs $100,000.

preventive maintenance on mining trucks

These lumbering vehicles operate under extreme loads and in extreme conditions, and it’s critical to keep them operating productively every single day. You need to anticipate problems so you can fix them before they breakdown, but how? You’re miles from anywhere.

Rio Tinto faces this scenario every day. The global mining operation, headquartered in London and with major operations in Australia and elsewhere, has the largest fleet of giant autonomous trucks in the world.

Its vehicles have transported more than 200 million tons of materials across approximately 3.9 million kilometers. That’s the equivalent of hauling approximately 3,500 Sydney Harbor Bridges or 540 Empire State Buildings to the moon and back five times.

So what happens when one of these vehicles breaks down in the middle of the pit?

On average, it costs the company $2 million per day in lost revenues for each out-of-service truck. You will often need to double that figure since the only way to get the broken truck out of the pit is to use a comparable working vehicle to tow out the damaged truck. So Rio Tinto’s cost is already $2 to $4 million per day, and it hasn’t even fixed the damaged equipment yet.

Keeping equipment up and maintenance costs down is a constant challenge for any mine operator. Or any other industrial facility that requires 24×7 operation.

The Answer: IoT-based Preventive Maintenance

Preventive maintenance based on the predictive power of analytics enables companies to fix vehicles onsite, before they fail, or at the very least drive a vehicle out under its own power. The preventive maintenance solution Rio Tinto implemented delivered an immense payback. And any company whose business and mission-critical systems face extreme conditions can reap similar rewards.

Rio Tinto’s goal was to increase efficiency, maximize safety, minimize staffing, and optimize output by networking its processes and equipment. A key part of the project involved automating its fleet of roughly 900 giant dump trucks with some 92 sensors placed on engines, drivetrains, and wheels.

The sensors track condition, speed, location, and more, and actually enable the trucks—which travel only on private land—to operate without human drivers and even optimize their routes to minimize fuel consumption.

In aggregate, Rio Tinto’s fleet generates approximately 4.9 terabytes of data per day. This information is used to not only control vehicle operation but also to enhance its efficiency. Preventive maintenance helps the company squeeze maximum life out of each piece of equipment. And these little gains add up to big benefits.

Most of the technology required to accomplish something like this already exists in the form of smart sensors, intelligent components, connectivity protocols, and software expertise.

Preventive maintenance depends on these IoT-enabled resources to capture and communicate information about your equipment. Perhaps a heat sensor detects a slight rise in engine temperature. Or a vibration is detected that might indicate a wheel going out of alignment.

 

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The system then analyzes that information in near-real time, using rules-based algorithms and deep learning capabilities to determine that the part has a 60 percent chance of failing within the next three weeks, for example. That information triggers an alert so that you can order parts and schedule the vehicle for servicing. With preventive maintenance, you fix a problem before it happens—not after it has wreaked havoc in your production schedule.

What’s Your Fast Path to Value?

Connected operations, remote operations, predictive analytics, and preventive maintenance: These are four tried-and-true paths to IoT payback. Your peers are implementing fast-payback IoT solutions across many industries—from agriculture to healthcare to sports and entertainment. In fact, I can’t think of any market where IoT is not being adopted today.

So how about you? If you haven’t yet started on the IoT journey, just pick one of these four fast path scenarios. Then start small to minimize the risk and maximize the value of your first project. Which of these is the best fit for your business?

Please share your thoughts in the comments below or on Maciej’s Building the Internet of Things community.