Improving mine-to-mill by data warehousing and data mining

Erkayaoğlu, Mustafa; Dessureault, Sean

doi:10.1080/17480930.2018.1496885

Cited by 14 publications

(7 citation statements)

References 10 publications

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“…Mine-to-mill optimization is a longstanding goal of the mining industry [1][2][3][4]. This approach focuses on optimizing the entire process around run-of-mine (ROM) material characteristics, rather than optimizing the unit operations to material characteristics individually.…”

Section: Introductionmentioning

confidence: 99%

A High-Fidelity Modelling Method for Mine Haul Truck Dumping Process

Young

Rogers

2022

Mining

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Dumping is one of the main unit operations of mining. Notwithstanding a long history of using large rear dump trucks in mining, little knowledge exists on the cascading behavior of the run-of-mine material during and after dumping. In order to better investigate this behavior, a method for generating high fidelity models (HFMs) of dump profiles was devised and investigated. This method involved using unmanned aerial vehicles with mounted cameras to generate photogrammetric models of dumps. Twenty-eight dump profiles were created from twenty-three drone flights. Their characteristics were presented and summarized. Four types of dump profiles were observed to exist. Factors that influence the determination of these profiles include the location of the truck relative to the dump crest, the movement of the underlying dump material during the dumping process and the differences in the dump profile prior to dumping. The HFMs created in this study could possibly be used for calibrating computer simulations of dumps to better match reality.

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Section: Introductionmentioning

confidence: 99%

A High-Fidelity Modelling Method for Mine Haul Truck Dumping Process

Young

Rogers

2022

Mining

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“…Related work includes the data-driven mine-to-mill framework proposed and tested in [19,20]. 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.…”

Section: Introductionmentioning

confidence: 99%

Digital Twins with Distributed Particle Simulation for Mine-to-Mill Material Tracking

2021

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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.

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“…Related work include the data-driven mine-to-mill framework proposed and tested in [Erkayaoglu(2015)] and [Erkayaoglu and Dessureault(2019)]. It was concluded that material tracking needs to be performed in a more comprehensive way to better connect mining and mineral processing data, and stockpile management, and the required infrastructure was found to be the main limitation for implementing the framework.…”

Section: Introductionmentioning

confidence: 99%

Digital twins with distributed particle simulation for mine-to-mill material tracking

Servin¹,

Vesterlund²,

Wallin³

2021

Preprint

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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 complex interplay between the equipment, control, and the processed material. The material properties have natural variations that are usually only known at certain locations. Therefore, we explore 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 can 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 makes it possible to better learn material properties from process observations, and to predict the effect on downstream processes. We test the technique on a mining simulator and demonstrate analysis that can be performed using data from cross-system material tracking.

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Improving mine-to-mill by data warehousing and data mining

Cited by 14 publications

References 10 publications

A High-Fidelity Modelling Method for Mine Haul Truck Dumping Process

A High-Fidelity Modelling Method for Mine Haul Truck Dumping Process

Digital Twins with Distributed Particle Simulation for Mine-to-Mill Material Tracking

Digital twins with distributed particle simulation for mine-to-mill material tracking

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