Yashar Pourrahimian, PhD, PEng
Mine Design, Planning, and Optimization
Summary of Contributions to Research and Practical Applications
Planning and production scheduling of any mining system has an enormous effect on the operation’s economics. Relying only on manual
planning methods or computer software that is based on heuristic algorithms will lead to mine schedules that are not the optimal global
solution. Improvements in computing power and scheduling algorithms over the past years have allowed planning engineers to develop
models to schedule even more complex mining systems. Consequently, it is now possible to formulate mathematical models that capture
the essential components of a selected mining method to generate a robust, practical, near-optimal schedule.
Underground mining
methods are characterized by complex decision combinations, conflicting goals and interaction between production constraints. Current
practice in underground-mine scheduling has tended toward using simulation and heuristic software to determine feasible, rather than
optimal, schedules.
My research in the area of mine planning and optimization focuses on:
- Optimization in surface mine design
and planning using operation research methods
Long-term, medium-term, and short-term
- Optimization in underground mine design and planning using operation research methods
Mathematical programming for sequence optimization
Mathematical programming for stope
boundaries optimization
Simulation optimization of mining systems
BLOCK CAVING
The economics of today’s mining industry are such that the major mining companies are increasing the use of massive
mining methods. Among the mining methods available, caving methods are favored because of their low cost and high production rates.
Improvements
in computing power and scheduling algorithms over the past years have allowed planning engineers to develop models to schedule even
more complex mining systems. It should be mentioned that, relying only on manual planning methods or computer software that is based
on heuristic algorithms will lead to mine schedules that are not the optimal global solution. Summary of contributions to research
and practical applications are as follows:
- Development of a practical optimization framework for production scheduling
of caving operation
- Introducing a multi-step approach for block cave production scheduling optimization
- Determination of the best
height of draw (BHOD) and development precedence in block-cave sequence optimization
- Presentation of a multi-index clustering
technique for the mathematical programming of block-cave production scheduling
- Determination of the optimal horizon for
production using sequential Gaussian simulation
- Optimization of block cave production scheduling under grade uncertainty
- Determination
of optimum drawpoint layout in block caving using sequential Gaussian simulation
- Development of a prototype open-source software
application with the graphical user interface (DSBC)
Control of fugitive dust emission on mine haul roads
Dust generated from mine haul roads poses
a severe health and safety threat to workers and the environment. Traditionally to control the dust, water has been applied on mine
haul roads. Although environmentally friendly, water lasts for a limited duration due to evaporation. As a result, water has less
longevity and requires consistent re-application, leading to an enormous waste of valuable water resources, especially in remote areas
where most mine sites are located. Currently, chemical suppressant has been proven by most researchers as a better palliation agent
in controlling dust, which is now adopted by many mining industries as a control measure. Among various environmental factors, the
temperature of the atmosphere plays an important role in how effective a chemical suppressant is at dust retention on mine haul roads
because temperature directly affects water evaporation. However, past and current research focuses only on the influence of hot temperatures
on the performance of chemical suppressants without considering other temperatures (i.e., cold and normal room temperatures).
Human factor and human error in mining industry
Human factors (HF) play an important role in the mining and mineral industry;
affecting operational and maintenance efficiency and safety. It is a well-known fact, even considering the introduction of new technologies
and automation in this sector, that a significantly large proportion of total human errors (HEs) occur during the operation and maintenance
phase. HE and HF in the mining and mineral industry is a subject which in the past has not been given the amount of attention that
it deserves. The aim of this research was to provide a comprehensive literature review of HF across several industries.
From this review, the impact of HF on operation and maintenance was summarized with a focus on what the mining industry is currently
doing and what opportunities for additional efforts in the HF area are.
New approaches for reduction of energy and emissions in mining industry
The purpose of this research is to demonstrate how
the mining industry can take a proactive role in reducing the intensity of its GHG emissions. Reducing GHG emissions does
not have to mean simply imposing extra costs; emissions reductions can actually be achieved along with increases in overall revenues
and profits. Many mining companies are committed to reducing their GHG emissions. However, one of the key challenges that they face
is the reality of increased stripping ratios and declining ore grades. Innovative approaches will need to be considered if mining
companies are to achieve any reductions in energy consumption and GHG emissions.
Developing an approach to generate a watertight mesh adaptive with cavity monitoring system (CMS)
Analyzing
stope monitoring data and modeling underground excavations is started with mesh generation on the data point sets. There are some
noise and concavity at the monitoring data points creating an error in mesh generation and accuracy of stopes modeling. Current mesh
generation methods and applications do not work accurately because they are not compatible with underground monitoring data and underground
extraction methods. Available methods pose errors in modeling and design calculation such as stope volume that is very important in
underground mine planning and scheduling. Therefore, we need a mesh generation method compatible with underground mining methods and
adaptive with monitoring data. The recommended mesh generation approach in this project should be compatible mathematically with underground
mining stope geometry and monitoring data set generating a watertight and accurate mesh.