Insights

Predictive vs. Preventative Maintenance: The key to unlocking ROI


Have you ever wondered what the difference is between predictive and preventative maintenance? Our VP of Customer Success, Chuck Tollman, delves into the subject and explores how mining companies are listening to machines to achieve greater efficiencies to improve the bottom line.

What is the difference between predictive and preventative maintenance?
Preventative maintenance is usually triggered by factors such as time, age, service recommendations, and meter readings — think of it like the scheduled maintenance you carry out on your car every six months or 10,000km. On the other hand, predictive maintenance is based on the actual operating condition of the equipment, rather than time or age factors.

How does predictive maintenance help customers get the best out of their systems?
Inside each machine is a wealth of information and this data tells a story. Our asset health software Trakka® 4.5 uses predictive maintenance to capture this information, report on the machine’s performance, and if problems are identified, allows time to schedule a service in advance to prevent machine failures before they occur. Asset health software is about listening, searching, locating, and taking action to fix an issue before it becomes a problem.

This approach to asset health can provide significant benefits for companies. On average, our customers achieve a 4:1 increase in ROI on parts alone.

A great example is a small surface mine we were working with in Nevada. They wanted to reduce their maintenance budget by 15 per cent. By listening to their machines through Dingo Software’s Trakka® 4.5 app were able to blow that target out of the water with a 24 per cent reduction in the very first year.

If you were in the driver’s seat of a large mining company, where would you start to improve asset health?
I would take it back to basics and apply the RAM process from the outset of acquisition. RAM stands for reliability, availability and maintainability. Its main objectives are to improve system productivity, increase overall profit, and reduce the total life cycle cost. It puts a real focus on being proactive, maximizing asset performance and extending the life of machinery.

What are your insights on current changes facing the industry?
Autonomous equipment is quickly becoming the future of mining. When you operate a piece of equipment, you act as ‘the eyes and the ears’ of the operation. When people are removed from the process, so too are factors like human emotion, experience and behaviour.

Although technology is playing a huge part in streamlining process, the element of human touch is something that cannot be replaced. Trakka 4.5 incorporates the best of both worlds, to combine a wealth of machine learning with a rich database of human experience.

What puts Dingo’s solutions ahead of the pack?
We believe in the expertise of our people — they’re the core of our operation. We understand that true efficiencies are about driving results at the bottom line. And that’s where we step in to help.

After 25 years working with customers from all over the globe, we recognise what adds the most value to their operations. A large part of this is partnering with our customers to listen, understand and work together to develop tailored solutions that meet their needs.

This allows our customers to focus on what’s important, while we filter through the massive amounts of data and turn it into useful information. The bottom line is, customers can make better decisions, boost asset availability and reduce daily operating costs.
 
Chuck Tollman
VP of Customer Success, DINGO