Inline Particle Analysis Technology in Mining – Anglo American customer testimonial

Anglo American, a global leader in the mining industry, has carried out various projects with the SOPAT technology in recent years. In May 2023, the first probe installation took place in the Mogalakwena mine.

As part of the FutureSmart Mining™ initiative, Anglo American is focused on addressing the industry’s sustainability challenges through innovative technology and partnerships that increase efficiency, reduce costs, and conserve energy.

One such innovation is Coarse Particle Recovery (CPR), implemented at the Mogalakwena platinum mine. CPR improves efficiency by floating larger particles, reducing energy use, increasing production, and recovering 80% of process water. It also addresses metal loss and minimizes water waste through advanced fragmentation, flotation, and dry stacking methods.

The photo-optical method analyzes various particle types inline based on image analysis in the range of 1 to 1200 micrometer. The system is connected with the plant’s process control system and delivers real-time data 24/7.

Recently, SOPAT sat down with Mashoto Mukhufi, Section Manager for Online Analytics at Anglo American, to discuss their experience implementing the particle analysis technology at their South African plant.

Could you start by telling us a bit about yourself and your role at Anglo American?

My name is Mashoto Mukhufi, and I’m the Section Manager for Online Analytics at Anglo American. I’ve been with the company for just under four years. In my role, I oversee online analytics across the processing divisions, from the concentrators to the smelters and refiners. My work includes discovering new solutions, testing them, validating their effectiveness, and providing post-implementation support.

Can you walk us through the process of how you identify and implement new technologies at Anglo American?

It’s quite a broad process. We start with a technology investigation—looking into what analytical techniques might suit the application we are considering. Once we identify the technique, we run small tests to gather data and ensure the analyzer is suitable for the specific process we want to optimize. This helps us decide if a particular technology will address our needs. Is very much like identifying where we can add value to the production teams, if we can have data available in real time rather than at a delayed time, for instance after a test in the laboratory.

Was it the first particle analysis technology you’ve implemented? How does it compare with other technologies you’ve used?

Yes, it was the first of its kind that we installed for this specific application. We’ve used other particle analysis technologies before, but it’s difficult to compare them directly because each serves different purposes. Some worked very well, others not so much, but the SOPAT technology stood out. The fact that it is an inline technique was the downfall to the others. We ran a successful pilot trial, which led to us choosing this technology for our CPR (Coarse Particle Recovery) application. We installed the probe directly into the production line, eliminating the need to take samples and dilute. In the years before, other technologies have caused delays due to transport, blockages and sample dilution.

Can you describe the CPR plant in Mogalakwena and how it was decided to monitor particle size for this application?

The CPR project is a different approach to flotation where we recover from coarse particles. You don´t need to grind the material in order to recover your valuable minerals from there. So the interest in terms of particle size is just from the feed side. We get the feed material from the initial flotation site. The interest of particle size is to see particularly on the lower upsize fractions what percentage of that is in the material and from that it can indicate whether the material is able to be used in the flotation in the CPR.

The tailings from the first flotation process go to the CPR and then whatever is suitable goes back to the primary flotation process.

Have you noticed any other benefits or challenges when using this photo-optical technology?

Yes, the inline capability is certainly a major advantage. Traditional methods like sieve analysis required more manual labor and transportation of samples, which added complexity. SOPAT has simplified that. However, one challenge we’ve encountered is that the data isn’t directly comparable to sieve analysis. The two techniques are inherently different, which can be hard to communicate to teams used to traditional methods. That said, the in-line technology provides a richer set of data. With image processing, we get more detailed information about particle size and shape, which offers valuable insights that we didn’t have before.

Also, it is important to point out that we have encountered challenges along the way, but what has been instrumental in this application is the constant and ongoing support to help us find a solution.

How about sustainability? Has in-line particle size analysis helped Anglo American in terms of saving costs or energy?

While we were still in the optimization phase before the plant was decommissioned, we were starting to see the potential for savings. One clear benefit is the reduction in lab work. With the in-line system, we can avoid taking as many samples, which saves both labor and time. While we haven’t yet quantified the financial benefits, in the long term, real-time data should contribute to both cost and energy savings.

Sustainability is certainly a key focus in the mining industry. Speaking of which, where do you see the future of the industry, and what trends are emerging in your area of expertise?

It’s a challenging time for the platinum mining industry. We’ve recently undergone restructuring, and the current market conditions are tough due to fluctuations in platinum prices. However, it’s cyclical. I believe that as we move forward, the industry will place more emphasis on operational efficiency, cost reductions, and sustainability. New technologies, which provide real-time data and reduce the need for manual sampling, are going to be crucial as we strive for greater optimization.