Bradken is working on a digital simulation model that has potential to revolutionise the way grinding mills are designed and operated.
Operational efficiency and sustainability are prime focus areas for the mineral processing industry.
Comminution, the process whereby rocks are crushed or ground into smaller fragments, is one of the most energy intensive processes on a mine site and poses a risk to achieving peak performance in these areas.
Bradken, a global provider of wear solutions, is working on a digital solution that will facilitate better liner designs for grinding mills, in addition to a myriad of other benefits for operators.
As part of a research collective led by the University of Newcastle’s Centre for Bulk Solids and Particulate Technologies, a research grant worth over half a million dollars was awarded by the Australian Research Council to create a digital twin of the grinding mill.
Bradken’s global research and development manager Reece Attwood says the potentially game-changing project will give global mining and resources operators the ability to precisely target grinding efficiency, mill liner service life, power consumption and carbon emissions, to optimise their operations.
“In the past few years our investment into simulation technology and the opportunity to refine and trial designs in that environment has helped improve efficiencies, but also demonstrated the importance of validation of such models,” he tells Australian Mining.
“With good inputs for simulation we can short cut the design cycle and optimise the customer’s operations more effectively and sustainably. This search by our engineers for accurate and measurable data, is what has driven the initiation of this research project.”
The project will be hosted by the University of Newcastle’s Institute for Energy and Resources (NIER), in collaboration with the University of New South Wales and the Commonwealth Scientific and Industrial Research Organisation (CSIRO), as well as international involvement from Delft University of Technology in the Netherlands.
It will combine a number of technologies, such as Internet of Things (IoT) instrumentation, enhanced simulation techniques and deep learning.
Attwood says good quality simulations can allow Bradken’s design engineers to trial solutions and optimisation options, to refine the final design and best understand the advantage each change has on the total mill operation before being sent to manufacturing facilities.
The simulation tool will benefit machine maintenance and upkeep, in addition to enabling the engineers to improve the design of existing and new grinding mills, according to Attwood.
“A simulation is only as good as the quality of the outputs, and any small modelling error can have a significant impact on the quality of predictions,” Attwood says.
“One of the key focus areas for this project is to reduce those errors as much as possible, meaning higher confidence process control and maintenance planning.”
Bradken’s existing preventive maintenance service to customers, known as ‘Vision Insight’, provides predictions on the remaining useful life of liners.
While accurate by today’s standards, Attwood says these predictions are based on empirical data and subject to confidence error that needs to be managed.
“Precise simulations will help us to pinpoint remaining useful life and assist the customer to optimise shut scheduling – to get more from their liners,” Attwood continues.
Bradken has already used this simulation technology to understand where opportunities for improvements are found.
The company has created products in collaboration with its customers using this simulation technology to help them hit their targets.
Attwood says Bradken recently demonstrated the improvements on a 40-foot semi-autogenous grinding (SAG) mill for one of its customers.
“Through design optimisation and validation with simulation technology, Bradken proposed a new mill layout and bullnose products that brought about a 25 per cent reduction in the number of bolts to secure the liners, as well as a 33 per cent reduction in the total number of liners,” Attwood says.
“The improvements increased the mill availability and provided an additional 15 hours of grinding.”
Attwood says the scope of the simulation project is broad and can, in the future, be developed to feed data into advanced process controls.
“There is always room for improvement in the minerals processing sector. For example, IoT and Artificial Intelligence (AI) are not new concepts. They are now buzz words because our ability to capture and process data has improved, and they will continue to improve into the future,” he concludes.
“It is the application of those technologies in new and innovative ways that will yield ongoing significant impacts, and that is what we are doing with this project – the application of machine learning as we are proposing to do has not been done before. We are excited to see the result.”