Dr. Yashar Pourrahimian

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.

Copyright © 2013-2019 Yashar Pourrahimian