Today, the mining industry is focused on chasing higher productivity from existing assets. Metso states: “Benchmarked against other process industries like oil and gas, mining is plagued by low utilisation of many of its fixed assets, fluctuating process performance, low energy efficiency, and high downtimes. All these are signs of a process with significant improvement potential. Use of data and AI is today seen as one solution for unleashing this potential. By collecting, analysing, and acting on process, machine, and sensor data, mining companies hope to identify and control the root causes of poor process performance. There is great promise and a lot at stake in turning the processing plant intelligent.”
Metso identifies three levers for data-driven process improvement:
(1) Stabilise the process by reducing variability
(2) Optimise the process against the constraints (eg for higher throughput or improved energy efficiency)
(3) Maximise equipment availability and uptime
Metso’s Jani Puroranta, Chief Digital Officer, states: “Advanced process control is a set of well-established technologies to address the first two levers. Taking control of the operations with an expert system that can handle the multivariate inputs and the often non-linear correlations between process variables is a must in the complex environment of a minerals processing plant. Once the process is under control, it can be optimized to be closer to the constraints to yield maximum performance. However, the third lever – maximizing equipment availability and uptime – often gets too little attention. Yet, no matter how streamlined your process is, if your assets are down, you will lose a lot of production. This is where cloud-based IoT and AI come in.”
This year, Metso is piloting a cloud-based IoT solution at multiple minerals processing plants in the USA, South America, Africa, and Australia. The record so far is at an African mine, where its remote condition monitoring solution has been up and running for a year already. “The results are quite promising. By analysing data from three connected Metso NordbergTM MP crushers, we have been able to identify certain failure modes and predict some failures ahead of time. I believe that it will not be long before we can start predictively maintaining these crushers based on actual and forecasted component wear.”
Going forward, Metso’s machines will become even better performing and reliable than they already are today. “We will be able to collect and analyses data from an increasingly wide variety of machines within the comminution circuit. We will also be able to predict – and prevent – a lot more of the different equipment failure modes. The machine designs will improve at a radically faster pace when the engineers who design and build the machines can see data from the machines and how they perform in the field in real-world conditions. Furthermore, we will be able to increase our customers’ crushing circuit performance, eg by optimising crushing efficiency and by retaining a more consistent particle size distribution.”