Resources

Insights

Top 4 Myths About Predictive Maintenance in the Mining Industry

May 14, 2021 | Insights

After working with mines from around the world for over 25 years, we’ve heard quite a few concerns – and misperceptions – about predictive maintenance. To help you understand the truth about predictive maintenance, we’ve addressed four of the top myths in this article.

Myth #1: “We can’t even do basic maintenance well, so there’s no way that we can do predictive maintenance.”

Implementing predictive maintenance isn’t predicated on doing traditional preventive maintenance well – or even at all. DINGO’s goal is to shoulder all the heavy lifting and maximize your current processes, so your team can focus on its tasks while implementing predictive maintenance for you.

Routine maintenance is usually triggered by breakdowns and fixed factors like time, age, service recommendations, and meter readings. The downside to preventative maintenance is that it’s easy to miss something if it occurs outside the scheduled maintenance window. Conversely, predictive maintenance is based on the actual operating condition of your equipment, so it’s continually assessing if everything is functioning well.

DINGO’s asset health software, TRAKKA®, captures predictive health information automatically from each of your machines, reports on performance, and if problems are found, schedules a service request in advance to prevent equipment failures. We maximize the data you already have – including preventive maintenance data − so an issue can be addressed before it becomes a problem.

Myth #2: “We already tried something like predictive maintenance, and it doesn’t work.”

There are different approaches to predictive maintenance and honestly, many don’t work well. Some mines rely on sensor data to understand which equipment needs attention. The downside is that sensor data is only part of the story – according to DINGO’s maintenance experts, over 80% of all problems are found via other condition monitoring sources.

Another challenge is that the amount of data gathered is often overwhelming and nearly impossible to analyze manually. On average, less than 1% of available data in the mining industry is being used – if that data was being intelligently utilized, it could prevent costly and time‐consuming equipment breakdowns.

DINGO’s Trakka ingests, curates, and analyzes data from almost any source while recommending actions to remediate issues. Using predictive analysis and machine learning, Trakka can ‘learn’ from patterns and make intelligent predictions based on the data.

TPM Software

TRAKKA predictive maintenance software makes it easy to analyze all condition data, including images and documents, in one centralized platform to improve insights, corrective actions and outcomes.

DINGO also believes that data analysis alone isn’t enough – human expertise also needs to be applied to troubleshoot and diagnose issues. Our team of Condition Intelligence experts has over 800 years of combined maintenance experience and manages the condition of over 150,000 vital components. They’ll review your condition monitoring data daily to identify issues and recommend corrective actions proactively. They will also continue to monitor the open problems until your equipment returns to a normal operating state.

Myth #3: “We’re already doing well enough.”

We’ve found that most mines don’t realize just how well they could perform if they had the right technology in place. Nearly every mine has room for improvement: based on data compiled from more than 50 mining operations globally, 33% of major components are regularly operating in a warning state and more than 11% are running in critical condition.

Inside each of your machines is a wealth of information. Predictive maintenance and asset health software are about listening, searching, locating, and acting to fix impending issues before becoming major problems.

A good example is a small surface mine we worked with within Nevada. They wanted to reduce their maintenance budget by 15%. By monitoring their equipment through Trakka, we reduced that target by 24% in the first year. This isn’t unusual: on average, DINGO customers achieve a 4:1 ROI on parts alone.

DINGO has helped hundreds of mining companies, so we have extensive real‐world experience in what constitutes doing “well enough.” We’ve compiled the world’s largest set of performance data on mining equipment components. This information is based on real‐world operating data, so it gives an accurate picture of your equipment’s performance. We can use this data to help you benchmark your mine’s current performance and define reasonable objectives for improvement.

Dingo operations

DINGO typically reduces maintenance costs by over $3 million per year at mid‐sized surface mining operations

Myth #4: “A predictive maintenance system will make me look bad.”

Our objective is to make you look good and become your trusted advisor.  We function as a partner in giving you the tools your mine needs to increase availability, extend component life, and reduce maintenance costs, so you get the credit and the pat on the back.

We understand you need a quick win, so our programs are geared towards bringing your overall fleet condition to an ideal health state within the first three months.  The typical payback with DINGO is greater than 4 to 1 within 12 months.

A mining customer had this to say about how DINGO helped him achieve his goals, “With Trakka, I can understand, manage, and reduce the cost for every run hour on a piece of equipment. Having all of our condition data in one place helps manage risk.”

At a large coal mining operation, a Maintenance Manager said, “Trakka’s information increases my confidence in my forecast and budget. Now that I understand my level of risk, I can do a better job of managing my budget and stretching things out confidently.  For example, if critical components are running well, I can take money that was scheduled for maintenance this month and shift that out for two months.”

Next Steps

Don’t let these myths about predictive maintenance hold your mine back from implementing a world‐class asset health program. DINGO can help your mine realize increased availability while extending component life and reducing operating costs by blending predictive maintenance technology with human expertise.

Contact DINGO for a brief Asset Health Consultation or use our Savings Calculator to estimate the annual savings that your operation could achieve.

businessman

“Trakka allows our team to run a highly effective condition-based maintenances program that helps our mine operate at the lowest cost per hour.”

– Maintenance Manager at a leading North American coal mine

More Resources Just for You

Power of Asset Health & Performance Dashboards

Power of Asset Health & Performance Dashboards

In order to gauge the ongoing performance of your predictive maintenance program and improve compliance, it's important to measure results that tie directly to your KPIs. Using asset health and performance dashboards, TRAKKA shows condition data from the operation...

read more
The Practical Application of Predictive Analytics

The Practical Application of Predictive Analytics

DINGO’s Trakka Predictive Analytics solution utilizes artificial intelligence and machine learning to predict impending equipment failures with confidence, allowing miners to proactively perform corrective maintenance actions to minimize downtime and optimize asset...

read more