Search Results (47)

Integrating autonomous haulage systems into underground mining has revolutionized safety and operational efficiency. However, deploying 3D detection systems for autonomous truck navigation in such an environment faces persistent challenges due to dust, occlusion, complex terrains, and low visibility. This affects their reliability and real-time processing. While existing reviews have discussed object detection techniques and sensor-based systems, providing valuable insights into their applications, only a few have addressed the unique underground challenges that affect 3D detection models. This review synthesizes the current advancements in 3D object detection models for underground autonomous truck navigation. It assesses deep learning algorithms, fusion techniques, multi-modal sensor suites, and limited datasets in an underground detection system. This study uses systematic database searches with selection criteria for relevance to underground perception. The findings of this work show that the mid-level fusion method for combining different sensor suites enhances robust detection. Though YOLO (You Only Look Once)-based detection models provide superior real-time performance, challenges persist in small object detection, computational trade-offs, and data scarcity. This paper concludes by identifying research gaps and proposing future directions for a more scalable and resilient underground perception system. The main novelty is its review of underground 3D detection systems in autonomous trucks. Full article

This study investigates the factors influencing the energy consumption and reliability of haul trucks in open-pit mines and quarries, where fuel costs and the environmental impact are significant. Traditional analysis of haulage systems often overlooks crucial aspects such as energy efficiency in the specific mining environment and the effect of road configurations on truck performance. As sustainability becomes increasingly important, reducing fuel consumption not only reduces costs but also reduces greenhouse gas emissions. A key focus of the study is the link between haul truck reliability and overall efficiency. Frequent breakdowns increase maintenance costs, lead to unplanned downtime, and increase fuel consumption, all of which have an impact on the environment. Reliable transport systems, on the other hand, improve efficiency, reduce costs, and support sustainability goals. The authors analyze the energy consumption of trucks in relation to vehicle performance parameters and transport route characteristics. Discrete modeling of the transport system showed the impact of the operating environment on the variability of energy consumption and vehicle reliability. The study highlights the importance of understanding specific energy consumption in order to optimize the choice of transport system, as transport costs are a major cost of resource extraction. By analyzing the effect of road quality on vehicle performance, the authors suggest that improvements to the road surface can more easily improve vehicle reliability and energy intensity than changes to other road design elements. The study presents a quantitative analysis of the impact of haul road conditions on the operational efficiency of haul trucks in mining environments. Through discrete simulation models, two scenarios were analyzed. Total operational time decreased by 11.2% when road quality improved, demonstrating the critical role of surface maintenance. Additionally, breakdown times were reduced by 44%, maintenance by 15%, and empty travel by 9% in the optimized scenario. These findings underscore the necessity of maintaining optimal road conditions to prevent substantial efficiency losses and increased maintenance costs. Full article

In light of the drawbacks of using fossil fuel, this paper investigates the competition between geographically spread charge point operators for future battery electric long-haul trucks along one of the busiest highways in Sweden. This is achieved using an agent-based model where trucks try to charge for a low price and still avoid queues in order to complete their transport mission. The charging need for a typical day at full electrification is derived from data from the Swedish Transport Administration. This typical day is simulated several times and in between these iterations the charge point operators adjust their prices and number of chargers, aiming to increase their profit. After a sufficiently long time of competition, a quasi-equilibrium is reached where, for example, prices and queueing times can be studied. The goal of the study is to estimate conditions for trucks and charge point operators in a future public fast-charging market. Assuming a price for electricity of 0.08 EUR/kWh, the results indicate that a system with low queuing problems is attainable with a mean price of 0.27 EUR/kWh or lower for public fast charging. It is also found that the behaviour of haulage companies, as a collective, can affect the future fast charging market to a great extent. If the hauliers are price-sensitive, they will be offered a low mean price, down to 0.11 EUR/kWh, but with queues, while if they are queue-sensitive, there will be almost no queues, but they will pay more to charge. Full article

Due to climate change risks, the public, regulators, and investors require solid actions to minimize the greenhouse gas (GHG) emissions of mineral extraction and metals production. The mining sector considers alternatives to reduce its carbon footprint by transforming the business and adopting new technologies into operations. Given the capital intensity, technical characteristics, and business structure involved, a shift in the mining industry necessitates impartial insights into the trade-offs and risks. Considering the low-carbon transition trade-offs and risks in mining, this study presents the application of system dynamics modeling (SDM) in mining projects to analyze the impact of decarbonization alternatives with respect to carbon footprint and costs. A system dynamics model of an open-pit copper mine is developed to quantify greenhouse gas (GHG) emissions, as well as capital and operational costs, during the project life cycle. The change in GHG emissions in the business-as-usual scenario with diesel equipment haulage versus the alternative scenario with electric overland conveyor haulage is compared concerning GHG emissions and associated costs. The results unequivocally demonstrated that electrifying material mobility offers significant decarbonization in open-pit mining if the on-site electricity has a low emission factor. The findings also indicate that the substantial cost difference between electrification and diesel alternatives is another major obstacle to implementing electrification in an open-pit copper mine. This research proves that implementing SDM in the mining industry can offer impartial insights into decision-making and enable a thorough evaluation of options using quantitative criteria. It effectively assesses and communicates the trade-offs and risks of transitioning to low-carbon alternatives because it analyzes project variables quantitatively and holistically and is easy to run. Full article

In mining, deposits are divided into blocks, forming the basis for open-pit mine planning, covering production and haulage route planning. Current studies often stage optimization and lack the consideration of road capacity, leading to suboptimal solutions. A novel approach integrates production scheduling and haulage route planning through a bilevel optimization model. The upper-level model integrates ore mining constraints to establish a mixed-integer production scheduling model, minimizing haulage costs. Spatiotemporal correlation constraints for block mining are determined using a two-stage algorithm. The lower-level model incorporates road capacity, forming a haulage route optimization model based on multicommodity network flow. A solution algorithm with a distance penalty strategy facilitates feedback between the upper and lower levels, achieving optimal solutions. Tested on a real open-pit coal mine with over 5 million blocks, this approach reduces haulage costs by 10.06% compared to stage optimization. Additionally, this approach allows for adjusting haulage demand in both temporal and spatial dimensions, effectively preventing road congestion. This study advances rational mining processes and enhances the efficiency of open-pit mining haulage systems. Full article

This paper presents an analysis of the impact of selected parameters of the operating environment on the energy consumption and reliability of haulage in surface mining. The analysis is based on a cyclic haulage system in a limestone open pit. The results of the calculations show that maintaining the operating environment in good technical condition has a positive effect on the haulage process and a direct or indirect effect on the operating costs, the analysis of which is also presented in the main body of the article. The analysis was carried out for a full year’s production, taking into account actual operating and maintenance downtime. The results of similar analyses can be used as a basis for deciding on the type of truck to be used for transport or for reconfiguring transport routes. In addition to the economic and operational aspects of energy consumption and reliability, the environmental aspect cannot be overlooked. The comparison of two variants of mining conditions shows that a modification of the haul road surface leads to a significant reduction in fuel consumption. Depending on the type of vehicle, fuel consumption can be reduced by almost 20%. The potential reduction in fuel consumption directly translates into lower exhaust emissions, which is an important element of an environmentally sustainable approach to mining transport, and greater reliability increases efficiency and reduces the carbon footprint of the vehicle. Full article

The selection of the optimal equipment for discontinuous haulage systems is one of the most important decisions that need to be made when an open-pit mine is designed. There are a number of influencing factors, including natural (geological and environmental), technical, economic, and social. Some of them can be expressed numerically, in certain units of measure, while others are descriptive and can be stated by linguistic variables depending on the circumstances of the project. These factors are characterized by a high level of uncertainty, associated with both exploration and mining operations. The experience, knowledge, and expert judgment of engineers and specialists are of key importance for the management of mining processes, consistent with the issues stemming from the dynamic expansion of open-pit mines in space over time. This paper proposes an integrated model that translates all the criteria that affect the selection of the optimal solution into linguistic variables. By employing the multiple-criteria decision-making method and combining it with fuzzy logic, we developed an algorithm that addresses all the above-mentioned uncertainties inherent in various mining processes where the experience of experts forms the basis. The fuzzy analytic hierarchy process is used in order to deal with trending decision problems, such as mining equipment and management system selection. The entire algorithm was applied to a real case study—the Ugljevik East 1 open-pit mine. Full article

Mining production, being one of the most energy-intensive industries globally, consumes substantial amounts of fossil fuels and contributes to extensive carbon emissions worldwide. The trend toward electrification and advanced developments in battery technology have shifted attention from diesel power to battery alternatives. These alternatives are appealing, as they contribute to decarbonisation efforts when compared to conventional diesel trucks. This paper presents a comprehensive review of recent technological advancements in powertrains for Mining Haulage Truck (MHT). It also compares these configurations based on mining system-level considerations to assess their future potential. The evaluated configurations include Diesel-Electric Truck (DET), Trolley Assist Truck (TAT), Battery-only Truck (BOT), Battery Trolley with Dynamic charging truck (BT-D), and Battery Trolley with Stationary charging truck (BT-S). According to the analysis, the energy demand for on-board diesel or battery power (excluding trolley power) in these alternative options is as follows: DET—681 kWh, BOT—645 kWh, TAT—511 kWh, BT-S—471 kWh, and BT-D—466 kWh. The paper also illustrates the theory of battery size design based on the current battery technology, battery material selection, battery package design, and battery size selection methods. In the case of tailored battery size selection, BOT, BT-D, and BT-S configurations require LiFePO₄ (LFP) battery masses of 25 tonnes, 18 tonnes, and 18 tonnes, respectively. Based on a techno-economic assessment of battery MHT alternatives with a future perspective, it has been determined that BT-D requires the lowest amount of on-board battery energy. Furthermore, over a span of 20 years, BT-S has demonstrated the lowest on-board battery cost. Full article

The aim of the research was to create a universal system for monitoring and evaluating the operating parameters of the haulage vehicles used for the haulage of wood with self-maintenance. The article presents partial results from the entire research. Data for research into the operational reliability of IVECO, SCANIA, and TATRA vehicles were obtained from the real-world operating conditions of two companies dealing with the mining/transportation process. Information from the operating conditions was obtained according to the test plan [n, R, t], according to which n objects were simultaneously tested, and the objects that were damaged during the tests were replaced with new ones; the tests ended after the test time t for each of the n positions. Based on the results and statistical analyses, it can be said that the best operational reliability is achieved by IVECO, followed by SCANIA, and only then by TATRA. The resolution of the above conclusions in operating conditions will contribute to the efficiency of the operation of the investigated facilities and the extension of the technical life of the means of transportation. Full article

This study proposes a novel approach for enhancing the productivity of mining haulage systems by developing a hybrid model that combines machine learning (ML) and discrete event simulation (DES) techniques to predict ore production. This study utilized time data collected from a limestone underground mine using tablet computers and Bluetooth beacons for 15 weeks. The collected data were used to train an ML model to predict truck cycle time, and the support vector regression with particle swarm optimization (PSO–SVM) model demonstrated the best performance. The PSO–SVM model accurately predicted cycle time with a mean absolute error (MAE) of 2.79 min, mean squared error (MSE) of 14.29 min², root mean square error (RMSE) of 3.79 min, and coefficient of determination (R²) of 0.68. The output of the ML model was linked to the DES model to predict ore production for each truck, section, and time period. Verification of the DES model demonstrated its ability to accurately simulate the haulage system in the study area by comparing production logs with the simulation results. This study’s novel approach offers a new method for predicting ore production and determining the optimal equipment combination for each workplace, thus enhancing productivity in mining haulage systems. Full article

The wear characteristics and related mechanisms of the Longwall Shearer Haulage System were investigated. Wear is one of the main reasons for failures and downtimes. This knowledge can help solve engineering problems. The research was carried out at a laboratory station and a test stand. The publication presents the results of tribological tests carried out in laboratory conditions. The aim research was to select the alloy intended for casting the toothed segments of the haulage system. The track wheel was made by the forging method using steel 20H2N4A. Haulage System was tested on the ground using a longwall shearer. Selected toothed segments were subjected to tests on this stand. The cooperation of the track wheel and toothed segments in the tootbar were analyzed by a 3D scanner. Debris chemical composition was also appointed, as well as mass loss of toothed segments. The developed solution toothed segment an increase in the service life of the track wheel in real conditions. The results of the research also contribute to reducing the operating costs of the mining process. Full article

The innovative transportation system is a pertinent need for the mining industry. Truck haulage is currently the most common mode of mineral transportation between the excavation sites and end use plants. However, besides being resource-intensive and inefficient, this mode of transportation accounts for a high number of accidents and injuries. In order to reduce the occurrence of accidents, it is important to first understand the primary contributors to truck-related occupational risks and then develop strategies to eliminate such risks. The available literature predominantly advocates for the use of statistical or probabilistic methodologies that suffer from considerable limitations. This paper utilizes the Fuzzy DEMATEL (Fuzzy Decision-Making Trial Evaluation Laboratory) approach to conduct an in-depth assessment of the critical factors that result in mining accidents involving trucks and the relationships between these factors, presented using a cause-and-effect diagram. The study also includes a sensitivity analysis for validating the robustness of the fuzzy model. The results show that high speed and aggressive driving is the most important causal factor behind accidents. The negative impact on socio-economic conditions of local community members is also discussed. Among other preventive measures, the paper emphasizes the pipe conveyor system as an alternate and safer mineral transportation system. Full article

This paper investigates the economic consequences of a haulage company replacing its line-haul diesel trucks with battery-electric ones. It also examines how large truck batteries should be, whether the haulage companies should use public fast chargers to complement their own, and whether public fast chargers have the potential to be profitable. The potential extra cost of losing payload capacity is estimated and there is an investigation of whether a charge-point operator should meet the peak demand for charging. The case under analysis is designed to represent a typical line-haul service between terminals in a major logistics system, with the finding that, in this case, a transition to battery-electric trucks seems cost effective for the company. Moreover, it is advisable for the company to use public fast chargers and these will likely become profitable given that the utilisation factor of the investigated public fast chargers may realistically exceed 20%. Full article

This paper presents an unsteady coupled heat transfer model in mine air and surrounding rock mass in the presence of distributed heat sources. The case of distributed heat sources is typical when analyzing the temperature distribution in mine excavations equipped with conveyor systems. For this case, the asymptotic value of the air temperature at the end of the mine excavation is determined not only by the heat exchange between the air and surrounding rock mass but also by the thermal power of distributed heat sources and the total airflow. This conclusion is confirmed by the experimental data presented in the paper for a longwall in a potash mine. We formulate the mathematical model and calculate the distribution of air parameters along the length of an excavation, considering heat release from the conveyor and surrounding rock mass. The results show that a distributed heat release is necessary for correctly calculating the air temperature in working areas. The numerical simulations allow us to recommend a redistribution of air between the haulage and conveyor roadways in the presence of distributed heat sources. Full article

Longwall shearers’ haulage system of the Eicotrack type, used most often nowadays, is presented in this article. Its disadvantages, causing problems with a correct operation of mechanized longwall shearer systems, are discussed. The concept of the innovative Flextrack, which should reduce the occurrence of the disadvantages mentioned above, is described. A course and research results, connected with rig tests of the Flextrack haulage system functionality, are presented. Measurement results of wear and stresses, obtained for the Eicotrack and Flextrack haulage systems, are compared and presented. Based on an analysis of the obtained results, a modified version of the Komtrack haulage system was suggested and manufactured. This haulage system was tested in the field conditions, similar to underground conditions in a mine coal longwall. The obtained results confirmed its full functionality and lack of problems experienced in the case of the Eicotrack and Flextrack systems. At present, the Komtrack system is tested in a coal longwall in Piast coal mine, where comparative tests with the Eicotrack system are conducted. The big part of the results presented in this article was developed as part of the research project KOMTRACK jointly implemented by KOMAG Institute of Mining Technology, AGH University of Science and Technology, Łukasiewicz Research Network—Cracow Institute of Technology, Specodlew Innovative Foundry Company and Polish Mining Group Inc., co-financed by the European Regional Development Fund (Contract No. POIR.04.01.04-00-0068/17). Full article