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Thesis submitted to the School of Mining and Geosciences of Nazarbayev University in Partial Fulfillment of the Requirements for the Degree of


Academic year: 2023

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Any contribution to research by others with whom I have collaborated at NU or elsewhere is explicitly acknowledged in the dissertation. The block caving mining system is the most economical underground mining system known today, and its popularity in the mining industry continues to grow. The block caving mining system can be described as the preferred mining system of the future because it lends itself to automation.

One of the most arduous tasks in block caving operation management is monitoring dilution at withdrawal points. It is hypothesized that LIBS could be adopted for underground land mining applications for monitoring dilution at withdrawal points in block caving operations. This application will increase the accuracy of measurements, remove the intensive use of labor and time of geologists at withdrawal points, reduce the costs of the block cave mining system and increase the safety of operation.

I would like to express my gratitude to Dmitriy Dikun for his contribution to the course of the study by helping with 3D modeling.


  • Problem Definition
  • Objectives of the thesis
    • Main objectives
    • Specific objectives
  • Hypotheses of the thesis
  • Scope of Work

The main aim of the thesis is to solve the problem of monitoring dilution at draw points in mines using the block cave mining technique. The specific objective of the thesis is conceptual development for the application of space laser beam rock analysis to detect dilution at draw points in block caving mining operations. For the replacement of geologists in the deepened mines, knowledge of the state of the art of block caving operations and traditional sampling processes is crucial.

The components of the system required are determined and a design is made for the automated sampling system. This design will serve as a basis for building a 3D model of the automated sampling system. This sampling system model will produce a 3D simulation in a small part of the mine that represents the extraction level of the block caving.

Conceptual development of the alternative to traditional manual sampling in block cave mines is presented in this thesis.


  • Block caving operation
  • Mine automation and robotics
    • Advantages of block caving
    • Disadvantages of block caving
  • Dilution control in block caving operations
  • Grade control in underground mines
    • Sampling in block caving: grab sampling
  • Spectroscopy: laser induced breakdown spectroscopy
  • The chemcam instrument: key features
  • Application of libs instrument to sample analysis
  • Drawpoint automation

For block heights above 500 meters, the prediction of production grade for each drawpoint is dependent on how fractured rock moves in the direction of the drawpoint in relation to surrounding rocks as well as on the ore reserve's initial grade distribution (Moss, Klein and Nadolski, 2018). Dilution is the result of the addition of waste rock to ore going to a processing plant, and it is largely attributed to the mining of waste found in the ore body, waste mining at the boundary between the ore and waste, and inaccuracy in waste classification ( Dagasan , 2018). Dilution control is a challenging task that requires a large amount of time and effort to solve, this view is supported by Diering et al (2018) who investigated dilution cases in the Palabora mine operated by the block cave method.

A successful quality management system prevents dilution and accurately determines the weight and content of the material to be processed (Dagasan, 2018). Monitoring of withdrawal points aims to prepare information on the quality of the material to be recovered from the withdrawal points. According to Booth et al (2004), the visual assessment approach works by visually distinguishing between mineral and waste, in cases where the color, shape or texture of the sample can be used to distinguish mineral from waste.

In the mines where the density of ore and tailings differ significantly, the density-based approach for grade control is applied. Next, the ore to waste ratio in the LHD bucket is measured using the bucket weight reading. The question of representativeness has long been a source of dispute among persons actively involved in the discipline.

To spread out sample distribution, geologists can draw a grid to the surface of the rocks at feature points that show where samples will be collected (Ross, 2012). Rapid measurement of the concentration of valuable metal in the field during the different stages of mine production is one of the revolutionary innovations, the implementation of which will be a significant leap forward (Rifai et al, 2017). Grant, Paul and O'Neill (1991) researched the application of the LIBS technology to iron ore.

The ChemCam instrument is part of the Curiosity Rover, which was deployed on Mars in 2011. According to Melikechi et al (2013), the analysis does not require sample preparation, which is the biggest advantage of the LIBS instrument over others. The laser pulse removes all the dust from the surface of the sample by hitting the rock 30-50 times in general.

In the mining industry, elemental analysis and material recognition are essential because the entire productivity of mines depends on this information.

Figure 2. The Henderson mine
Figure 2. The Henderson mine's extraction level plan (Rech, Keskimaki and Stewart, 2000)



Risk assessment and risk control

Contingency plan

To avoid misuse of references leading to unintentional plagiarism, the MEA report writing guidelines are taken as the basis for writing the thesis. The report covers all types of references and the correct use of references to the works of other authors. To avoid data loss in Word, the function of automatic saving of changes will be enabled.

The Blender program has the quality of dropping out of the application without saving the data due to complex calculation processes.


  • Required resources for the thesis
  • Research process
  • Design of the robotic system
  • Building a 3D model of the robot
  • Building a 3D model of extraction level
  • Developing 3D simulation of the sampling process

A robotic sampling system will be developed on the basis of the Curiosity Rover and will be composed of two parts: mast and body units. But the fewer polygons, the better the performance of the animation and the computational resources will be reduced. Low polygon modeling does not result in a fully detailed model, but rather allows a stylistic geometric recreation of the desired model.

The wheels were made on the side of the rover and then using a "mirror" feature duplicated on the other side. A suspension system is also made on both sides of the main body to connect the wheels to the body. Creating a 3D model of the mine extraction level is necessary to show the robot during the sampling process.

A small area of ​​the mine with ore in drawpoints was modeled in Blender software to represent the extraction level of the block cutting operations for this purpose. The extraction level classification of the El Teniente mine was chosen for the model as one of the most popular extraction techniques. By choosing the “Faces” button on one of the sides of the cave we can show the entrance to the extraction level.

Instead of being smooth, the tunnel walls look like real mine tunnels. After working out the model of the extraction level, the next step is a modeling of the pile of hollow rock at the draw point. Then it is necessary to set up physical parameters to provide cutting properties for breaking the UV ball.

This process is demonstrated by shooting a laser from the robot's mast at the rocks in the pile. Blender enables automatic simulation of the movements of the model and the camera (which follows the rover).

Figure 10. Methodology diagram of the proposed R&D.
Figure 10. Methodology diagram of the proposed R&D.


At the draw point, which has a span of 4.7 m and a height of 5.2 m, the robot takes up little space and has plenty of room to maneuver. When the robot reaches the draw point and reaches the pile of hollow stones, the sampling process begins. At each draw point, the robot must perform sampling using a LIBS spectrometer that mimics manual sampling by geologists.

Using the same techniques as geologists, the robot will shoot at specific locations in the cave stock, replacing the sampling grid in it. However, for each mine, the sampling network will be established by the geological department according to the geological characteristics of the specific mine. After completing the sampling process at one draw point, the robot moves to the next draw point, and so on.

The number of maximum traction points that the robot can reach depends only on the capacity of the battery installed in the robot. Compared to a geologist for whom the maximum coverage of the draw point is limited to the number of samples he or she can carry, the robot can take a larger number of samples if provided with proper maintenance and timely battery replacement . The robot's computer must always calculate how much the robot can use the battery.

If the charge is low, it should go to the nearest service center, where the service staff will replace the uncharged battery with a charged one. A robot traveling from the first pull point to the next is shown in Figure 22. An audible signal system and lights on the front and back of the robot will alert employees when the robot is approaching.

Due to the fact that each worker has a tracking device, a special program will be built into the robot's computer to prevent the robot from directly approaching the worker by stopping the robot when it detects a signal from this device. To prevent dust or water from entering the system, the robot will be completely sealed, and all devices will be built into the body.

Figure 20. The robot system at drawpoint.
Figure 20. The robot system at drawpoint.


For each mine, the sampling grid will be established by the Geological Department according to the geological characteristics of specific mines. A geologist will travel from one draw point to another in about 30 seconds at an average speed of 5 km/h. The speed of the robot will be determined by its electric motor and can reach speeds of 15-20 km/h, so the journey will take less than 10 seconds.

As a result, a robot will spend less than two minutes sampling two gullies, while a geologist will spend more than an hour. Current technology allows the use of remotely controlled equipment that can be operated by a worker far from the mine. The robot system manufacturer will provide a repair warranty and if the laser or other parts of the robot break down, they will send workers to repair the laser and the complex systems in the robot.

A training program for mine maintenance staff at the producer is also an option.




Kuzmin, E V, Uzbekova, A R, 2006 Hollowing of ores in underground mining: a textbook (M.: . Publisher of Moscow State Mining University).


Figure 1. Example of block caving system (Brannon, Carlson and Casten, 2011)
Figure 2. The Henderson mine's extraction level plan (Rech, Keskimaki and Stewart, 2000)
Figure 3. Example of draw column caving process. Numbers from 1 to 10 are represent each drawing zone with  height of 20 m (Stewart, Allman and Hall, 2010)
Table 1. Types of sampling for various underground mining methods upon mining production stages

Ақпарат көздері


Table 1 – Variables description Symbol Variables Proxy Dependent variable ROA Return on assets Net income/total assets Independent variables Size Bank Size Logarithm of Total