Faculty of Engineering and Technology
https://repository.biust.ac.bw/handle/123456789/109
This collection is made up of electronic theses and dissertations produced by post graduate students from Faculty of Engineering and Technology2024-03-28T19:34:34ZAssessment of underground mine production efficiency at Morupule coal mine
https://repository.biust.ac.bw/handle/123456789/515
Assessment of underground mine production efficiency at Morupule coal mine
Mosiamisi, Otsweletse
Mining productivity is a measure of the effectiveness of mining resource inputs computed
as a ratio of production output per input resources. Factors affecting productivity can be
grouped as a combination of technical and economic factors. The ratio of the production
outputs to inputs in a mine determines the mine’s productivity. The greater the output
produced at optimum cost, the more efficient is the functional mine system. In this study, the factors affecting mine production efficiency at Morupule Coal Mine (MCM) were assessed using statistical analysis methods as the mine has varying daily production levels that are mostly below set threshold targets. Also, production shift variances were assessed and the causes of productivity variances were classified according to scale of impact. The results show wide variances in the production outputs between morning, afternoon and night shifts; the equipment availabilities for continuous miners (CMs) ranged from 79.5% to 92.2% and those for shuttle cars varied from 84.0% to 92.0%.
The average engineering availabilities for CMs and shuttle cars were generally higher than their set threshold targets but they are the lowest performing equipment’s. The regression models show a high goodness of fit between the parameters and mine production showing that there is a strong correlation between them. It is recommended that the CMs should be frequently examined to be within their equipment reliability period and the duration of the mean time to repair of shuttle cars should be improved to ensure they are serviced within the maintenance service threshold targets.
Thesis (MEng of Engineering in Mining Engineering--Botswana International University of science and technology, 2021
2021-06-01T00:00:00ZFall of ground characterization and its implications for ground control at BCL mine
https://repository.biust.ac.bw/handle/123456789/514
Fall of ground characterization and its implications for ground control at BCL mine
Phumaphi, Pako Tumelo
Mining at great depth is associated with many principal stability and ground control problems. One of the challenges currently facing underground mines is changes in ground conditions leading to the fall of ground (FoG) hazards. Fall of ground refers to rock material dislodged from roof and sidewalls of an underground excavation usually unintentionally induced. This study focuses on FoG characterization. A FoG database has been compiled. In order to quantify the rock mass behavior around underground excavations and fully characterize the FoG events, statistical analysis, numerical methods, rock engineering system (RES) and artificial neural networks (ANN) have been used. The Bamangwato Concessions Limited (BCL), an underground mine located in Selibe-Phikwe, Botswana was used as case study where FoG events that occurred in various stopes and other mine openings were recorded. Overall, two aspects of the FoG characterization were investigated. In the first part of this thesis, the concept of ground behaviour index was introduced to predict the ground class associated with FoG hazard. To this end, ANN was used to determine the weights of input parameters involved and the RES was employed as a tool to quantify the non linear interactions of parameters via the interaction matrices and the hazard class evaluated. Meanwhile, in the second part of the thesis, numerical modelling was implemented to analyse the modes of rock failure around the underground openings which had led to FoG. Several models were established in Rocscience software package to simulate the structure-induced and stress-induced failure modes or a combination of both that had been observed in the field. In general, the obtained results were in agreement with the field results. It is concluded that this study has enhanced the understanding of ground conditions, fall of ground characteristics and provided ground control improvements in BCL mine.
Thesis (MEng of Engineering in n Geological Engineering-Botswana International University of science and technology, 2018
2018-07-01T00:00:00ZDesign, modelling, and simulation of a vision based automatic gold panning system
https://repository.biust.ac.bw/handle/123456789/513
Design, modelling, and simulation of a vision based automatic gold panning system
Makoni, Blessing Chipfurwe
To do away with the hazardous, tedious, repetitive, and export-dependent gold panning
procedure currently practiced by artisanal and small-scale miners in developing countries
an automated system for the gold panning procedure is presented in this thesis. Gold panning is one of the gravimetric separation processes which separate particles of greater specific gravity (particularly gold) from mineral waste. This separation method is prevalently used in low-tech areas and mercury is incorporated to make for effective and efficient gold recovery. The mercury used exposes the miners to hazardous health conditions and increases mercury pollutions. Little technical effort and knowledge are available to provide solutions adaptable to the African context. This study is devoted to the technical optimization of the gold washing process and hand-picking process involved in the current panning procedure through mechanization and automation. The design was achieved through the use of the V model for mechatronic system design (VDI 2206 guidelines). Morphological analysis was used to adapt and make use of the already existing concepts and designs to mechanize and automate the manual, expert-dependent, and tedious gold panning process. The design adopted was based on the usage of visual data to control the separation and picking process.
In the automation of the gold panning process and robotic handling, it is important to
identify and locate the gold particles in the images captured by the image sensor. Color
image thresholding in the CIELAB color space was developed as a front-end technique to
automate the visual feature identification and localization of gold particles in the pan. 3D
CAD models of the designed system were developed in Solid works. Finite element analysis of the designed washer concept was performed in ANSYS 2019 to precisely calculate material stress, strain, deformation, contact, and safety factor. This was done to predict the behaviour of the components and assembly under given boundary conditions and loading in a quasi-real scenario. Kinematic modeling of the handling system was performed using the Denavit Hartenberg convention and analytical methods. Physical modeling using MATLAB, Simulink, and SimScape was done to perform dynamic modeling and simulations of the handling system. Stateflow charts were developed to model state machines and flowcharts which were used in task planning to interface various components used in the vision-based control and picking process. Simulation and modeling results showed that the design is feasible, achievable, and efficient.
Thesis (MEng of Engineering in Mechatronics and Industrial Instrumentation--Botswana International University of science and technology, 2021
2021-07-01T00:00:00ZPrediction of fuel consumption of haulage trucks in open pit mines
https://repository.biust.ac.bw/handle/123456789/512
Prediction of fuel consumption of haulage trucks in open pit mines
Tadubana, Gomolemo Kaone
Fuel consumption by haulage trucks is one of the costliest components in open-pit mining.
Reducing fuel consumption by trucks could lead to large savings in materials handling costs. This study sought to investigate the factors that affect fuel consumption by haul trucks and to propose an algorithm for predicting fuel consumption by trucks in open-pit mines. Case Based Reasoning (CBR) methods namely case-based reasoning using forward sequential selection (CBR-FSS), traditional CBR and Naive techniques were used to predict fuel consumption using datasets from Komatsu and Caterpillar trucks operating at Orapa Mine. The results show that the CBR method can be used to predict fuel consumption by trucks in open-pit mines; the predicted values of fuel consumption using the CBR-FSS technique gave better results in terms of much lower absolute residual values on all the datasets used, gave higher standardised accuracy values and effect sizes than the other prediction techniques. Thus, the CBR-FSS can be used as a mine planning tool to predict fuel consumption using available data from the previous trips.
It is recommended that mine managers use the CBR method in predicting fuel consumption by haulage trucks to reduce fuel costs and identify trucks with high fuel consumption for early maintenance work to be done on them. Finally, larger datasets from other mines with effects of weather should be used in future studies to improve the accuracy of the predictions and make the findings more applicable to all conditions in open-pit mines.
Thesis (MEng of Engineering in Mining Engineering--Botswana International University of science and technology, 2021
2021-03-01T00:00:00Z