What is Predictive Maintenance in Mining?

In mining, equipment failure isn’t just frustrating. It’s expensive, disruptive, and often dangerous. When a key piece of machinery breaks down, everything stops. It can delay production, impact delivery schedules, and profit margins take a hit.

According to a 2023 ABB survey, unplanned downtime costs industrial businesses an average of USD $125,000 per hour globally.

That’s why more mining operations are starting to rely on something smarter: predictive maintenance.

Instead of reacting after something goes wrong, predictive maintenance helps you catch problems early. It gives you the chance to fix issues before they lead to breakdowns, lost time, or unnecessary costs. It’s a safer and more efficient way to manage equipment, and it’s quickly becoming the new standard across the industry.

Understanding Predictive Maintenance

Predictive maintenance uses real-time data to monitor the condition of equipment. It helps you determine when a machine is likely to fail, so maintenance can be scheduled only when it’s truly needed. It’s similar to a car warning light coming on before something goes wrong, giving you the chance to fix the issue before it causes serious damage.

This approach is different from older methods like:

  • Reactive maintenance, where you wait for something to break before fixing it.
  • Scheduled maintenance, where parts are replaced or serviced at regular intervals whether they need it or not.

In mining, predictive maintenance is especially valuable for equipment under constant pressure, such as vibrating screens, motors, gearboxes, and hydraulic systems. These are critical to production, and when they fail unexpectedly, the costs can quickly add up.

The aim is straightforward: reduce unplanned breakdowns, extend the life of your equipment, and make better use of your maintenance team’s time.

How does Predictive Maintenance Work?

Predictive maintenance systems use sensors to track the condition of key components over time. These sensors measure things like vibration, temperature, pressure, and oil quality, which can all point to early signs of wear or failure.

The data collected is sent to a central dashboard or monitoring system. Maintenance teams can review trends, receive alerts when values move outside expected ranges, and make decisions based on real equipment conditions rather than fixed schedules.

In some setups, predictive algorithms also use historical data to forecast when a part is likely to fail. This helps teams plan maintenance at the right time, avoiding unexpected breakdowns and reducing disruption to production.

Why it Matters in Mining

Mining is tough on equipment. The work is heavy, the environment is harsh, and everything is remote, which makes it expensive and difficult to fix things when they break. Predictive maintenance gives teams the ability to act early, avoid breakdowns, and keep production running smoothly.

Here’s how it helps mining operations stay on track:

  • Fewer breakdowns
    By spotting problems early, you can avoid unplanned downtime on critical equipment like crushers, conveyors, or screens. That means fewer disruptions and lower emergency repair costs.
  • Longer equipment life
    Machines that are maintained based on real operating conditions last longer. Predictive maintenance helps you avoid running parts too long or replacing them before it’s necessary.
  • Lower maintenance costs
    You only service what needs attention. This cuts down on labour hours, spare parts usage, and unnecessary shutdowns.
  • Better safety
    Early detection of wear or damage reduces the risk of major failures that could lead to injury or environmental impact, especially in remote or high-load areas.
  • Smarter use of resources
    Less energy wasted, fewer materials used, and more efficient workflows contribute to stronger sustainability outcomes and improved ESG performance.

Real-time Oil Condition Monitoring in Action

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Above: Tan Delta OQSx-G2 Oil Quality Sensor installed on equipment.

At Oreflow, we help mining clients install real-time oil condition monitoring systems using Tan Delta technology. These sensors provide instant, accurate insights into equipment health while machines remain in operation.

For example, a vibrating screen motor fitted with a Tan Delta sensor can alert operators when oil quality starts to degrade due to contamination or wear. This allows maintenance teams to act before damage occurs, helping prevent costly unplanned downtime.

With live data at their fingertips, operators can see exactly what’s happening inside critical components – no lab tests, no guesswork. Just reliable, real-time information that supports better decisions and safer, more efficient operations.

Want to see how this works in the field? Check out Tan Delta’s case studies to see predictive maintenance in action.

Want to Learn More?

If you’re curious about how predictive maintenance could reduce downtime and save your company money, we’re happy to help. Our team can walk you through how real-time oil condition monitoring works and how it fits into your operation.

Contact us today or visit our Tan Delta Systems page to get started.