You can’t manage what you can’t see, and in mineral processing plants, that means keeping a close eye on your process data. But how fresh does your data really need to be?
It all depends on what you want to do with the data. Older, aggregated data can be useful for tracking long-term trends, but some decisions should be made based on data from today, not a week ago.
For plant control processes like grinding, flotation, and separation, data should be as close to real-time as possible. For example, if you can quickly detect changes in your ore feed, you’ll have a much better chance of increasing both throughput and recovery.
Many plants rely heavily on historical data, collected using manual spreadsheets and older databases. But new software platforms make it easy to get fresh data faster which helps metallurgy teams run their plants more efficiently than ever. So, what are the limitations of historical data in mineral process plants and what software options are now available?
The limitations of historical data
Drew Clements, Optimisation Team Lead at Mipac, says historical data is useful for any kind of analysis, but production planning requires more timely information.
“If I’m looking from a reliability perspective, the older the data and the more data I can have is great,” Drew says. “If I’m trying to run a plant, the time frame that I need to look at is quite different.”
Most software tools used in process plants—including SCADA and DCS systems, AVEVA PI Process and PI Vision—only provide historical data because they are designed to monitor and trend past throughput, not give real-time insights.
Process plant operators need up-to-date insights because the nature of the ore body is unpredictable. As the ore material changes, processing needs to keep up.
“It’s like the superannuation ad disclaimers,” says Drew. “Past performance is no reflection of what’s about to happen in the next 24 hours. What we process today will not be the same as what we processed yesterday.”
Getting current data
In the past, metallurgists sampled incoming ore and made process adjustments based on lab test results. This required them to wait for lab test results which took too long and slowed down decisions.
Modern process plants can now easily be set up with precise instruments onsite (such as cameras on belts), paired with sophisticated analytical software.
“With things like Courier online instrumentation, within three minutes of the sample being taken, I can know the grade passing through and can make much more precise changes,” Drew says.
Tying these instruments into control loops allows you to automate the process so that it responds in real-time.
“If you can make those changes now, instead of waiting hours for a sample result, there’s a lot of opportunity in terms of what you can extract that you would otherwise have lost.”
Process control systems + software
To do this properly, you need a system that can integrate data from multiple sources onto a single real-time dashboard.
Drew says you need to start thinking not just about today’s ore but also about what might be coming next week. Tools such as the MPA software suite are better suited than historian platforms to integrate data from multiple sources, provide advanced analytics and help you make proactive decisions.
“When I joined the mining industry 20 years ago, we were looking at yesterday’s performance to try and make changes today,” Drew says.
“Now, with Edge AI and more predictive tools, we can try and predict the mineralogy before it even gets here, to make changes to the plant ahead of any change.”
Integrated systems such as the MPA software suite, RtDuet and AVEVA Production Management can not only predict what’s going to come down the belts but also forecast necessary maintenance. To do this, they monitor the hardware via sophisticated instrumentation and also adapt by learning how skilled and experienced operators react.
“Predictive analytics can predict the reliability of machinery,” Drew says. “Algorithms pick up patterns from old school operators like me and predict that, for example, a pump is going to fail within a certain time frame.”
This advance warning allows operators to schedule maintenance without risking unexpected and costly downtime.
3 steps to begin using software in your plant
So how do you go about introducing new software tools into your plant to make your data more up-to-date? Drew suggests three key steps to getting started with a more integrated approach:
1. Start with an instrument audit
“The first thing I would always start with is an instrument audit. The main reason is that, if you don’t, you could spend hundreds of thousands of dollars putting the software in, but it won’t work properly if the instrumentation is not good or poorly placed.”
2. Go through your automation pyramid
“The next thing to do is look at your control loops and your historians. You’ve got your automation pyramid, where each layer is an enabler for a higher level of automation, and you’re just moving up levels in that pyramid. So you start with the base layer of instrumentation. Next, level your control loops and then things like historians.”
3. Advanced control
“Finally, you move on to the digital side, looking at things like the MPA software suite, AVEVA PI Vision, RtDuet or AVEVA Production Management. As you get to that point, you may find you need to review your level of instrumentation again. It might cost a bit more to address that, but it will save you maybe two or three times as much by improving recovery and grade as well as reducing logistics costs.”
The end of short-termism
Drew says while some plants might baulk at the initial outlay, getting access to faster, more integrated data will justify short-term pain for long-term gain.
“Once you show people there are better ways to use their data, even historical data, to start making data-driven decisions, you’ll find it straightforward to justify the improvements and show the return on investment,” Drew says.
“I did that with a plant in Africa where we made some significant changes to their milling and the return on investment was more than 2000%. No one’s going to believe that, but it’s true.”
In short, for many areas in a mineral process plant, the fresher the data the better. New analytics tools are a small step towards giving operations managers the data they need. Getting real-time, accurate data not only makes the plant more productive but gives operators a chance to use their skills more effectively, putting production targets in easy reach.
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