Year

2023

Degree Name

Master of Philosophy

Department

School of Mechanical, Materials, Mechatronic and Biomedical Engineering

Abstract

Traditional methods of rock extraction for hard rock mines revolve around the use of explosives, such as drill and blast. The use of explosives for rock extraction imposes many safety and environmental issues. The Komatsu MC51 hard rock mining machine is designed to solve these issues. The machine uses a 5 axis boom with an eccentric mass connected to the tool tip that oscillates at a frequency of 60 Hz. The oscillating disc uses the theory of undercutting to break rock and propagate fractures lying under the surface of the rock. The machine tool tip follows a set path created by an operator and the generated trajectory is extrapolated over a single machine ‘sump’ (lateral depth). This method of trajectory generation still poses a need for an operator. The use of Artificial Intelligence (AI) in the mining industry has recently started to gain traction. In this study real world MC51 data was collected and analysed as well as data from the mine and testing facilities, including rock properties. Using sensors as inputs for an AI algorithm, mainly high-definition Complementary Metal Oxide Semiconductor (CMOS) camera and Light Image Detection and Ranging (LiDAR), in house designed algorithms are used to create new trajectories for the MC51 boom to follow. Google OR tools and its submodules of Constraint Programming and Vehicle Routing are the sub modules focused on in this study.

FoR codes (2020)

4017 Mechanical engineering, 4014 Manufacturing engineering

This thesis is unavailable until Wednesday, March 05, 2025

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Unless otherwise indicated, the views expressed in this thesis are those of the author and do not necessarily represent the views of the University of Wollongong.