Search Documents

By Alireza Kamrani, Yashar Pourrahimian, Hooman Askari-Nasab

In-pit crushing and conveying (IPCC) is an option to decrease the enormous operating costs that a truck shovel can introduce in an open-pit mine. Finding the best locations for the IPCC over the mine life will impose a new set of requirements for the mine planning. Through a two-step mathematical programming model alongside the road network, this method finds the optimal in-pit crusher locations and relocation times first and then optimizes the long-term mine schedule. The model is verified by a real mine. The results show that the truck travel time could be reduced by 500% and the discounted cash flow increased by 8% with an optimized schedule considering the crusher placement.

Jun 25, 2023

By Javad Sattarvand, Amin Moniri-Morad

Predicting equipment failure behavior plays a critical role in providing a safe operation. Although various reliability evaluation methods are available for estimating failure behavior profiles, these approaches are based on mathematical formulation, leading to actual operation simplification and improper estimation of failure trends. This study proposes a discrete-event simulation (DES) approach to model fleet failure behavior. This approach can model the maintenance strategies in multi-component systems with minimum simplifications. In this regard, the first step was to collect a historical failure time dataset (e.g., the time between failures). Then, the DES model is established to predict the severity of failure events and design maintenance strategy considering actual operation circumstances. Afterward, the maintainability analysis was performed to estimate equipment downtime and availability. The achieved results showed that the system availability was about 85%. Also, the findings demonstrated that the DES could efficiently predict the equipment failure behavior using various stochastic events.

Jun 25, 2023

By Cuthbert Musingwini, Adeodatus S. Nhleko, Mahlomola I. Mabala

Optimization of a three-dimensional (3D) underground stope layout is complex given the number of variables and constraints to consider, such as the stope size. Determination of the appropriate stope size in stope layout optimization problems is a complex process that must consider several factors including placement of infrastructure and development, production scheduling, and equipment selection. An inappropriate stope layout can result in unrealistic expectations for a production schedule, consequently negatively affecting the derived economic value. Therefore, this paper used a dual interchange algorithm (DIA) to evaluate the effect of stope size on the stope layout economic value (SLEV) for a synthetic Platreef mineral deposit planned for extraction using sublevel open-stoping. The results showed that generally as the stope size increases, the SLEV decreases. This aligns with practical mining because larger stope sizes have a higher chance of incurring more dilution which reduces economic value, while smaller stope sizes enable more flexible extraction where unprofitable blocks can be left unmined as waste, thus increasing the derived SLEV.

Jun 25, 2023

By Robert Bissonette, Samir Sbai

A critical component of implementing autonomous systems is the ability to use information from a robust sensory and information system to make sound, predictable, and repeatable decisions to assure safety. This means that any such system would need to evaluate what objects (people, equipment, boulders, etc.) of interest exist in that environment (with relevant data about identity, trajectory, characteristics, etc.), project a future continuum of those objects (including considerations for variabilities), and make control intervention choices to minimize risk due to exposures in the present operational area. The components of an overall system would include: a) sensor and data fusion, b) probability projection of future states, c) generation and evaluation of alternate futures, and d) implementation of best course of action to reduce risk. The National Institute for Occupational Safety and Health (NIOSH) Spokane Mining Research Division (SMRD) is studying this framework for applications for autonomous mining equipment. This paper focuses on using information from the sensor fusion engine to generate a continuous projection of future and alternate states (b and c above) incorporating the factors of confidence, accuracy, tolerance, and other variabilities. We refer to this as Machine Situational Awareness (MSA).

Jun 25, 2023

By Jan Luca Grunow, Ansgar Bendiek, Klaus Böde

According to the Markowitz portfolio theory the value of a diversified portfolio is higher than the sum of the parts of a portfolio, which is an important consideration for the correct valuation. This is valid for real estate portfolios as well as for mining assets (or enterprises). This paper analyses the application of the portfolio theory to a diversified portfolio of assets in the real estate industry and draws conclusions on further research work to be done in the minerals industry. The volume of real estate transactions is increasing over recent years. As such, the nature of those transactions is constantly changing and in some cases portfolios become more heterogeneous as they are composed of different property categories, e.g. locations and types of use. This makes their economic evaluation more difficult. This paper focuses on the acquisition of a fairly heterogeneous real estate property portfolio purchased by “Commerz Real” in Germany in Q4 2019. For economic evaluation the widely used Markowitz portfolio theory (Markowitz, 1952) was applied. It was investigated whether diversification effects could achieve added value in the form of a reduction in risk compared to the sum of their individual components. As a result the findings of this research could be applied to other heterogeneous real estate transactions and even to mine property portfolio or PPP1 project portfolio transactions.

Jun 25, 2023

By Enrique Jelvez, Nelson Morales Varela, Christian Ihle, Joaquin Silva

All mineral beneficiation processes require water for its execution. Therefore, the availability and adequate management of water are key to the existence of any mine operation. However, many mines’ operations are affected by water scarcity and risk an increase of operational costs or even production in some cases. This paper proposes a model to minimize the losses of water due to evaporation and re-absorption by adjusting the active and inactive periods of the discharge in different points of the tailing. When applied, the model determines optimal or nearly optimal discharge operation in all the scenarios that were evaluated.

Jun 25, 2023

By J. Sattarvand, P. C. Augustine

Despite significant safety improvements, the mining industry remains one of the most hazardous occupations globally and the evacuation of Miners, when an uncontrollable incident occurs in the mine, is the best bet to saving lives. However, Human factors/behaviors during an emergency are likely to influence the evacuation performance. Other industries have made a significant effort to determine these human factors that can impede evacuation performance, however, the current state-of-the-art in mine evacuation or self-rescue is that the evacuation route is predetermined, and a static sign is used to direct miners to the predetermined safe location. This method is limited in representing actual conditions that arise in a real emergency, neglecting the different behaviors displayed by humans. As optimization of the evacuation of a mine plays a fundamental role in emergencies and modeling evacuation behavior and movement of miners is a complex task, this research utilized Agent-Based simulations to simulate the evacuation behavior and performance. It was observed that people with the smart evacuation device made fewer mistakes and arrived at the safe place in less time compared to those have no access to the device. The Mathematical model used in optimizing the shortest path to a safe place is also explained in this paper.

Jun 25, 2023

By Amy McBrayer, Andrea Brickey

Limited research has been conducted related to the development of mathematical optimization models for production scheduling at large surface coal mines using the area, i.e., strip, mining method. Increased economic and technical challenges have led to a new interest in production schedule optimization models for these type of mining operations like those currently applied to model underground and open pit mines. While area mines share similar characteristics to both open pit and underground metal operations, neither an open pit nor underground production scheduling model adequately depicts an area mine mathematically. We present an integer programming model with blending constraints and discuss the challenges and opportunities related to the implementation for area mines as well as future research in area mine production scheduling.

Jun 25, 2023

By Błażej Doroszuk, Robert Król

Mill drums are essential equipment in various industries for the comminution of materials. To optimize their design and operation for efficient and cost-effective processing, it is necessary to understand the behavior of the mill drum under various operating conditions. This study investigates the behavior of a mill drum using a combination of experimental and numerical methods. The factors that can influence the behavior of the mill drum, such as the size and shape of the mill, grinding media, rotational speed, filling level, and material properties, are discussed. Experimental methods can be limited in obtaining measurements of internal processes, so numerical methods such as the Discrete Element Method (DEM) are also used to simulate the behavior of the mill drum. In this study, the experimental measurements of the motion of the grinding media are obtained using computer vision methods, and the numerical simulations are calibrated using the experimental results. A designed experiment approach is used to evaluate the performance of the mill drum under various operating conditions. The results of this study can be useful for the design and optimization of mill drums to achieve better performance and energy efficiency.

Jun 25, 2023

By W Medina, G Angulo, A Anani

A current challenge faced by the mining industry is solving the integrated transition mine problem (TMP) that maximizes the net present value (NPV). This study aims to develop an optimization framework capable of solving the TMP. The problem is NP-hard and therefore computationally intractable. Three ad hoc approaches – Exact solution, Benders’ decomposition, and Benders’ decomposition with Bienstock-Zuckerberg (BZ) algorithm – are compared for different scheduling periods. The TMP is formulated as a mixed integer linear programming model, implemented in Python, and solved with the Gurobi optimizer. The results showed that Bender's decomposition with the BZ algorithm outperforms the other approaches in execution time, computational cost, and feasibility to address large problems in exchange for a marginal cost in the quality of the NPV obtained. In addition, the probability of finding the optimal point of transition is higher regardless of the number of feasible crown pillar locations evaluated. This is achieved through the optimality cuts proposed in the algorithm.

Jun 25, 2023

By Bartłomiej Bursa, Paweł Stefanek, Paweł Stefaniak, Sergii Anufriiev, Wioletta Koperska, Maria Stachowiak

The article presents the main functionality of the DSS class system for monitoring and stability assessment of tailings storage facilities. The presented demonstrator was deployed on the example of the Żelazny Most reservoir - the largest active facility of this type in Europe and the second one in the world. Considered a high-risk structure, it demands a system capable of online analysis of big data from various sources using machine learning, 3D modeling, or GIS mapping with the functions of interactive time-spatial analysis. In this paper, we present a complex calculation module with an integrated user interface.

Jun 25, 2023

By Kate Willa Brown Requist, Eric Lutz, Moe Momayez

As air quality sensor networks become increasingly popular in underground coal mines, it is important to generate paradigms for the application of the collected data. To date, air quality sensing has been primarily used as an early warning system for hazardous air conditions. Using data collected from a network of sensors in a US underground coal mine, we have created multiple visualization methods to show the interactions of carbon monoxide evolution with ventilation airflow. These visualization methods can allow for further analysis of the source of contaminant, as well as better data resolution across the area of concern within the mine. By utilizing univariate spatial interpolations, we present methods for identifying the movement of carbon monoxide at one-minute intervals. The resulting visualizations display the evolution of carbon monoxide concentration across a sizeable study area over a period of 14 minutes.

Jun 25, 2023

By Milka Madahana, John Ekoru

Particulate matter is one of the leading pollutants in the mines and in the communities in the areas near or surrounding the mines. The availability of large Clinical and environmental data sets obtained from the mines has brought about the need to use better approaches to analyze the collected data. Prediction and control of particulate matter concentration in the mining environment is essential in minimizing air pollution and protecting the respiratory health of mine workers. The main objective of this research work is to analyze datasets obtained from a mining area using machine learning techniques which will then be followed by the real-time estimation of dust particulate in the mines. Datasets collected over 8 years in an hourly sampling rate from an open cast mine is cleaned and analyzed for trends and patterns. Artificial Neural Networks (ANNs), Support Vector Machines and decision trees techniques are applied to analyze and predict the particulate concentrate. The estimation of particulate concentration using Artificial Intelligence will significantly contribute toward the development of quantitative tools to be used in correlating of cause and effect of dust concentration in mines. The results obtained in this work will form a sub-unit of a respiratory health monitoring system for mine workers. The system is essential in the collection, analysis, and tracking of mine workers’ respiratory health, thus it forms part of an early intervention system for mine workers. From the existing theory, we expect the Artificial Neural Network will perform much better than previously used classical models.

Jun 25, 2023

By Brendan Demich, Linda L. Chasko, Brendan Macdonald, Timothy J. Orr, Jessie J. Mechling, Cassandra Hoebbel, Jason Navoyski, William Helfrich, Jessica Cohen, Paul E. Schmidt, Jennica L. Bellanca

The National Institute for Occupational Safety and Health (NIOSH) in partnership with the Mine Safety and Health Administration (MSHA) developed VR Mine Rescue Training (VR-MRT). It is a training platform that allows mine rescue team members to explore virtual emergency scenarios collaboratively. Team members use a head-mounted display to visualize and interact together with equipment, hazards, and dynamic ventilation. All player actions are recorded and displayed for debriefing. Researchers at NIOSH demonstrated the training platform at various mine rescue competitions, including the International Mine Rescue Competition, and collected feedback. Participants’ responses were overwhelmingly positive. This paper describes the development of the software platform and the results of the usability surveys and interviews.

Jun 25, 2023

By Josiah Pohl, Christopher Utter, Kyle Everly, Akshay Chowdu

Battery Electric Vehicles offer increased energy efficiency for open-pit load & haul operations at a potentially lower overall carbon cost. Electrifying a mine’s fleet, however, presents a unique set of operational challenges. In this study, we explore the effects of electrification on productivity at real operations using a Discrete Event Simulator. The model can simulate multiple shifts, a mixed fleet of diesel and electric trucks, charging and refueling stations, trolley systems, and accurate shovel-truck loading cycles. This study helps determine the trade-offs of adopting electric fleets and how they interact with the layout of today's mines.

Jun 25, 2023

By Augusto Andres Torres Toledo, João Felipe Coimbra Leite Costa, Luciano Nunes Capponi, Diego Machado Marques

Short-term mine planning to open pit requires defining diglines to orientate the excavation geometry. In deposits with multiple chemical variables, it is necessary to have more rigorous control over the feeding of the processing plant. This study analyzes the impact of incorporating multiple chemical variables, the risks generated by geological uncertainty, and the number and starting point locations of shovels in the sequential design of diglines. The objective is to maintain and preserve the low-grade variability, required tonnage, and continuity in sequentially selecting blocks. To achieve this, the probability distribution function of each chemical variable is used while attempting to maintain the ore grades as constant as possible. As it is difficult to maintain multiple elements with low variability simultaneously, the relevance of each chemical variable in the economic benefit is identified. Weights are assigned to signal the importance of each element based on its significance in the recovery process. Several diglines, consisting of sequential blocks, were generated on the same seed point to meet the weekly ore demand. Optimizing the stationarity of multiple chemical variables, accessing and reducing the geological uncertainty performed through geostatistical simulation of grades and transfers functions, considering the number and location of shovels, while meeting the operational restrictions of the selected blocks. The optimized digline with the multiple grades as stationary as possible is retained. The process is illustrated in a phosphate mine. The results show that the proposed method is viable and allows for a quick solution.

Jun 25, 2023

By Amin Mousavi, Soroush Khazaei, Yashar Pourrhimian

As a factory-like method, sublevel caving consists of development activities, stockpiling and production activities that are carried out on different levels independently. Therefore, considering the operation from the development phase to the plant will lead to more reliable production scheduling. This paper presents a mixed integer linear programming framework for the long-term production scheduling of sublevel caving that maximizes the net present value while satisfying development activities, mining, and processing capacities, continuous mining, the allowable number of active mining units, grade blending, and vertical and horizontal sequencing. The model is coded in Jupyter Notebook and is solved using the CPLEX solver.

Jun 25, 2023

By Theophilus Mensah, Kwame Awuah-Offei

Engineers face significant challenges when determining what geometry provides the most profitable and safe stope for extraction. Several techniques and optimization algorithms have been developed in recent years, but most fail to find optimal solutions because they are heuristic or LP-based without efficient geometric constraints. This paper presents a two-dimensional binary linear programming (BLP) model for determining the optimal combination of blocks in a stope that maximizes the economic value of the layout of stopes for a sublevel deposit. The work draws from Queyranne and Wolsey’s (2017 & 2018) formulations of tight constraints for bounded up/down times in production planning problems to formulate novel and efficient geometric constraints along with geotechnical and grade constraints for the BLP stope layout optimization problem. Results from the model indicate that it is possible to formulate efficient shape constraints in LP-based approaches. The model used for the numerical example contained 144 valuable blocks out of 774 blocks, which translates into an economic value of $53.21M. The BLP model selected 60 valuable blocks and 13 waste blocks that met all constraints translating into a maximum economic value of $34.4M in 1.83 hours within a gap tolerance of 0.00%.

Jun 25, 2023

By Artur Skoczylas, Paweł Stefaniak, Sergii Anufriiev, Wioletta Koperska, Maria Stachowiak

In many underground mines the excavated ore is produced during the blasting process. Drilling machines that are used to drill the blastholes, where later the explosives will be mounted, are crucial for this task. In order to optimize the currently used techniques, great emphasis is placed on increasing the efficiency and safety of blasthole drilling operations. The natural consequence is the development of monitoring systems and algorithms for processing operational and historical data. In this article, we present the result of the analysis of drilling data carried out as part of the IlluMINEation project. The paper proposes an algorithm for work cycle detection for drilling machines, together with the estimation of general operating parameters and diagnosing the drilling process on the basis of long-term data. Based on the available data, selected components of the drilling cycles have been indicated. Several approaches based on the parameters of the defined cycles are proposed. These approaches can be used in the future to create a full-fledged system for examining the effectiveness and safety of mining drilling rigs.

Jun 25, 2023

By Jorge Amaya, Nelson Morales Varela, Francisco Saavedra, Gonzalo Nelis, René Gómez

Precedence constraints are broadly used in mathematical models and algorithms for mine planning to model, for example, slope angles in open pit operations or connectivity in underground mines. Unfortunately, these constraints do not capture relevant geometrical aspects for the design of the mine like minimum bottom space of pits or smoothness of the economic envelope in block caves. In this work, we present different approaches that utilize precedence constraints generating economic envelops that are more suitable for design purposes. The numerical experiences show that the proposed techniques produce high value envelops with better geometrical properties and that the methods proposed can be computed efficiently.

Jun 25, 2023