Abstract
Systems for transport and processing of granular media are challenging to analyse, operate and optimise. In the mining and mineral processing industries, these systems are chains of processes with a complex interplay among the equipment, control and processed material. The material properties have natural variations that are usually only known at certain locations. Therefore, we explored a material-oriented approach to digital twins with a particle representation of the granular media. In digital form, the material is treated as pseudo-particles, each representing a large collection of real particles of various sizes, shapes and mineral properties. Movements and changes in the state of the material are determined by the combined data from control systems, sensors, vehicle telematics and simulation models at locations where no real sensors could see. The particle-based representation enables material tracking along the chain of processes. Each digital particle can act as a carrier of observational data generated by the equipment as it interacts with the real material. This make it possible to better learn the material properties from process observations and to predict the effect on downstream processes. We tested the technique on a mining simulator and demonstrated the analysis that can be performed using data from cross-system material tracking.
Highlights
One reason is that it requires an elaborate digital infrastructure for collecting, processing and communicating data between edge devices, distributed control systems and centralized data services
We explored digital twins with distributed particle simulation, of systems doing transport and processing of granular media
A digital twin of a mine may be realised as a system of particle simulations, distributed over virtual assets that evolve according to their physical counterparts using real-time particle simulation where no real sensors or control signals are available
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. When the material reaches blind spots in the system, for example a silo or a stockpile, the digital copy is driven by a simulation model fed with data from the control system and available sensors in real time. It was concluded that material tracking needs to be performed in a more comprehensive way to better connect mining and mineral processing data, as well as stockpile management, and the required infrastructure was found to be the main limitation for implementing the framework. A closed-loop framework for real-time reserve management was introduced in [21] It incorporated sensor-based material characterisation, geostatistical modelling under uncertainty, data assimilation for a sequential model updating and mining system simulation and optimisation. No previous work was found where material tracking was performed using a particle representation
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