Shovel Performance Research Articles

“Optimizing mine management: integrating lean theories and short interval control in surface mining”

ABSTRACT Frontline supervisors are pivotal in mining productivity, but face challenges due to the long working hours and rapid decision-making skills required. This paper proposes the application of Short Interval Control (SIC) to streamline information flow and support decision systems in mining, by developing a framework that aims to improve shovel performance during critical hours. Initial results demonstrated improvements in shift change and reduced operational disruption due to lunchtime breaks. Conclusively, although the methodology didn’t translate directly to significant improvements due to data availability, it became evident that SIC can help identify deviations and facilitate quick shifts within operational mining processes.

Effect of grain size distribution of blasted rock on WK-35 shovel performance

Effect of grain size distribution of blasted rock on WK-35 shovel performance

Research on the Trajectory and Operational Performance of Wheel Loader Automatic Shoveling

In the automatic shoveling operation of wheel loaders, the shovel trajectory has a significant influence on the operation’s performance. In order to obtain a suitable shovel trajectory and optimize the automatic shovel performance of the loader, we developed a test platform for the operational performance of loaders. Nine parallel shoveling trajectories of different depths were designed according to the coordination shoveling method. The formula for calculating the operational performance is established. The automatic shoveling test is performed according to the designed trajectory to obtain the real-time shoveling parameters, which are then combined with the calculation formula to calculate the operating parameters of the loader. Finally, the actual range of operational performance parameters is calculated by the normal distribution. The test results show that the trajectory with a shovel depth of 400 mm is the optimal trajectory. It was also verified by comparing manually controlled shoveling with it. With only a 1% difference in the full bucket rate, the operation time of automatic shoveling was 15.3% less than manually controlled shoveling, fuel consumption was 4.7% less, the energy consumption of practical work performed was 10.7% more, and maximum operation resistance was 20.5% lower. Therefore, the operational performance of the loader following this trajectory for shoveling meets the actual requirements.

Autonomous and Operator-Assisted Electric Rope Shovel Performance Study

Automation has been changing the mining industry for the past two decades. Material handling is a critical task in a mining operation, and truck-shovel handling systems are the primary method for surface mining. Mines have deployed autonomous trucks, and their positive impact on both production and safety has been reported. This paper aims to study the extent to which autonomous and operator-assisted loading units could improve different aspects of a mining operation. Four different levels of automation ranging from operator-assisted swing and return to fully autonomous for a shovel were considered. A discrete event simulation model was developed and verified using detailed data from a shovel monitoring system. Later, the developed model was deployed to assess how each of the proposed technologies could improve productivity and efficiency. Results show that up to a 41% increase in production can be achieved. Both mining companies and equipment manufacturers can use the methodology and results of this study for future decision-making and product development.

Application of MR and ANN in the prediction of the shovel cycle time, thereby improving the performance of the shovel-dumper operation - A case study

Loading and hauling of ore and waste are the key operations of an opencast coal mine and entail a high operational cost. The productivity of a mine can be increased by reducing the cycle time of loading equipment as well as utilizing dumpers optimally. In this paper we discuss the impact of rock type, bucket fill factor, rock fragmentation, the height of the cut, and angle of swing of the bucket on shovel performance. A time study is conducted on shovels in an opencast coal mine with experimental blasts of rocks to assess the impact of different factors on the performance of the shovel. Based on the data, the authors applied multiple regression (MR) and artificial neural network (ANN) techniques to develop different models for the prediction of the shovel cycle time. Developed models are validated by comparing the predicted data with actual field data. With the help of the best model, the plausible fleet size is determined in order to utilize the shovel and dumper optimally and to improve the performance of shovel-dumper operation.

Simulation and optimization of the tracked chassis performance of electric shovel based on DEM-MBD

To study and optimize the tracked chassis performance of electric shovel performance. First, the sand-gravel pavement model is built based on the discrete element method (DEM), and the virtual prototype model of the electric shovel is established. On this basis, the impacts of the pre-tension force, the road-wheel spacing, the sprocket speed, and the grouser height on the tracked chassis performance are explored by the coupling method of DEM and multi-body dynamics (MBD), and the performance prediction model of tracked chassis is obtained through Kriging interpolation method. Finally, taking ground pressure distribution, power, and track tension as the optimization goal, multi-objective optimization based on genetic algorithm (GA) and performance prediction model of tracked chassis is implemented, and the corresponding optimization values are 21,028 N, 1.10 rad/s, −12.97 mm, and 9.50 mm. The feasibility of the optimization results is then confirmed via comparison with results of DEM-MBD simulation, the results show that the power and tractive force are reduced to varying degrees, and the ground pressure variation coefficient and track tension are increased.

Modeling the influence of electric shovel operator performance on mine productivity

ABSTRACT Truck-shovel systems are commonly used for material handling during surface mining. Not only does the overall outcome of a mine rely heavily on haulage system performance, but it constitutes a significant portion of mine operational costs. Using detailed data from a shovel monitoring system, this study statistically analyzes variations among key performance activities by shovel operators. Based on the results, a novel operator relative score system is introduced. To quantify the extent to which different aspects of a mining operation could be influenced by shovel operator practices, an operator discrete event simulation sub-module was developed and verified. Results showed that operators could affect mine production, number of trucks, and queue times by up to 20, 16, and 41%, respectively. This simulation model can be used by mining companies to assess their current shovel performance and improve production by modifying shovel operator practices.

Hydraulic excavator versus electric rope shovel performance

Hydraulic excavator versus electric rope shovel performance

Performance Analysis of Log Extraction by a Small Shovel Operation in Steep Forests of South Korea

In South Korea, logs for low-value products, such as pulpwood and fuelwood, are primarily extracted from harvest sites and transported to roadside or landing areas using small shovels. Previous studies on log extraction, however, have focused on cable yarding operations with the goal of improving productivity on steep slopes and inaccessible sites, leaving small-shovel operations relatively unexamined. Therefore, the main objectives were to determine small-shovel extraction productivity and costs and to evaluate the impact of related variables on productivity. In addition, we developed a model to estimate productivity under various site conditions. The study took place in 30 case study areas; each area has trees with stems at a diameter at breast height ranging from 18 to 32 cm and a steep slope (greater than 15%). The areas ranged from 241 to 1129 trees per hectare, with conifer, deciduous, and mixed stands. Small-shovel drives ranged from 36 to 72 m per extraction cycle from stump to landing. The results indicated that the mean extraction productivity of small-shovel operations ranged between 2.44 to 9.85 m3 per scheduled machine hour (including all delays). At the forest level, the estimated average stump-to-forest road log production costs were US $4.37 to 17.66/m3. Small-shovel productivity was significantly correlated with stem size (diameter at breast height and tree volume) and total travelled distance (TTD). However, a Pearson’s correlation analysis indicated that stand density and slope did not have a significant effect on productivity. Our findings provide insights into how stem size and TTD influence small shovel performance and the predictive ability of productivity. Further, this information may be a valuable asset to forest planners and managers.

Bench Structural Integrity Modeling of Oil Sands for Optimum Cable Shovel Performance

The ultimate bearing capacity of bench and haul road formations are essential for the health and longevity of shovel crawlers. In soft saturated formations (especially in the Athabasca oil sands formation), heavy machines have been known to sink, resulting in production losses and high operating costs. Companies have solved these problems by widening the shovel crawlers to reduce average stresses on the formation, which may also be costly. In this study, the authors provide a solution to this problem using fundamental research. The Buisman-Terzaghi model is used to develop bench/haul road bearing capacities and their structural integrity within an oil sand formation at an environmental temperature of 25°C. A 3D finite element (FE) model of the formation is developed in ABAQUS to examine the average stresses and deformations on the formation at static equilibrium. The results show that the deformation of oil sand occurs during the first 30 seconds of crawler interaction. Two distinct regions were observed from the plastic strain failure pattern: the region below the tracks has larger strain at failure, and the regions adjacent the tracks expand deeper and wider in all directions. Failure of the formation was observed to occur mostly under the tracks and this progress non-linearly to the base of the formation. These failure patterns were triangular in nature and agree well as reported in Terzaghi’s early work on shallow foundation. The deformations were observed to be non-linear. The maximum static deformation of 2.497 cm was observed at the crawler-ground interface during the interaction. Future works would include a virtual prototype of cable shovel crawler-oil sand interaction to measure real-time stresses; crack initiation and propagation under dynamic conditions.

Efficient Cable Shovel Excavation in Surface Mines

The cable shovel is widely used in surface mining. High operating and ownership costs necessitate efficient use of the cable shovel. Operator practices have long been suspected to contribute towards the inefficient use of the shovel. Crowd arm and hoist rope speeds are key measures of operator practices. The objective of this work is to find the crowd arm and hoist rope speeds for optimal shovel performance for given initial conditions and material properties. Shovel kinematics and dynamic modeling, using shovel geometry and the simultaneous constraint method, respectively, have been employed to build models of the excavation process. Dynamic models of the shovel payload and the material cutting resistance have also been developed using geometric simulation and passive soil pressures techniques, respectively. These models are solved numerically by combining Runge–Kutta and Gaussian elimination algorithms to compute the work done and the resistive forces during shovel excavation. The algorithms have been combined into a shovel simulator. The simulator has been used to simulate the P&H 2100BL shovel. The simulation results indicate that input energy and digging time increase with increasing crowd arm and decreasing hoist rope speeds. The input energy per unit loading rate is proposed as an appropriate measure of shovel performance. High energy per unit loading rate occurs for high crowd speeds and low hoist rope speeds. For the simulated conditions and crowd arm and hoist rope speeds ranging from 0.25 to 0.5 ms−1 and 0.5 to 0.7 ms−1, respectively, the optimal crowd arm and hoist rope speeds were found to be 0.25 ms−1 and 0.7 ms−1, respectively, and the objective function value was 0.21 KJs/kg. This work establishes, theoretically, the fact that operator practices have an effect on shovel performance and is useful in establishing optimum practices. The results are the initial steps towards full automation of the excavation process.

Operator and dipper tooth influence on electric shovel performance during oil sands mining

A shovel performance monitoring study was undertaken in two oil sands mines operated by Syncrude Canada Ltd. using performance data obtained from P&H 4100 TS and BOSS electric mining shovels. One year of shovel performance data along with geological, geotechnical and climatic data were analysed. The approach adopted was to use current and voltage data collected from hoist and crowd motors to first identify dig cycles and then to calculate the energy and/or power associated with digging. Analysis of performance data while digging uniform material along with operator team schedules showed that the performance of a shovel can vary significantly depending on which operator is digging. Up to 25% variability in hoist power consumption and 50% variability in productivity was noted between different operators. Shovel type and dipper teeth configuration can also influence the power draw on electrical motors during digging.

Spatial variability of shovel dig performance

The analysis of real-time shovel performance monitoring data has been constrained to date by the application of conventional one-dimensional statistics. This article proposes the use of geostatistics to analyse the spatial variance of shovel digging performance. Four key performance indicators are used in the modeling: shovel payload, dig rate, payload frequency and shovel production. The data processing incorporates the implementation of ordinary kriging with specified variogram models. The graphical interpretation of the results obtained provides maps, which are a convenient tool for assessing shovel operating context, operator proficiency and muckpile characteristics. A case study is presented to illustrate the applicability of the new geostatistical approach.

Performance monitoring of electric cable shovels

A shovel performance monitoring study at an oil sands mine used current and voltage data from hoist, crowd and swing motors of P&H 4100 series electric cable shovels. The goal was to identify key shovel performance indicators using only data from the motors. It was found that hoist and crowd motor responses can be used to identify different shovel activities, especially the dig cycle. Some key shovel performance indicators examined are the dig cycle time, digging energy and digging power. By averaging the hoist power over a number of dig cycles, the average hoist power is less sensitive to digging trajectory and could be a useful parameter for assessing ground diggability characteristics. Analysis of performance indicators showed that the shovel performance can be significantly influenced by the operator. The study revealed that freezing temperatures can have a minor and localized influence on shovel performance.

Virtual prototype simulation of hydraulic shovel kinematics for spatial characterization in surface mining operations

Hydraulic shovels are large-capacity equipment for excavating and loading dump trucks in constrained surface mining environments. Kinematics simulation of such equipment allows mine planning engineers to plan, design and control their spatial environments to achieve operating safety and efficiency. In this study, a hydraulic shovel was modelled as a mechanical manipulator with five degrees of freedom comprising the crawler, upper, boom, stick, bucket and bucket door components. The model was captured in a schematic diagram consisting of a six-bar linkage using the symbolic notation of Denavit and Hartenberg (Ho and Sriwattanathmma 1989). Homogeneous transformation matrices were used to capture the spatial configuration between adjacent links. The forward kinematics method was used to formulate the kinematics equations by attaching Cartesian coordinates to the schematic shovel diagram. Based on the kinematics model, a 3D virtual prototype of the hydraulic shovel was built in the Automatic Dynamic Analysis of Mechanical Systems (ADAMS) environment to simulate the motions of the hydraulic shovel with selected time steps. The simulator was validated using real-world data with animation and numerical analysis of the digging, swinging and dumping motions of the shovel machinery. The superimposed display of the deployment of the hydraulic shovel in three phases allows a detailed motion examination of the system. The numerical results of linear and angular displacements of the bucket tip and bucket door can be used to analyse the kinematics motion of the hydraulic shovel for its optimization. This simulator provides a solid foundation for further dynamics modelling and dynamic hydraulic shovel performance studies.

Mechanics of cable shovel-formation interactions in surface mining excavations

The cable shovel excavator is used for primary production in many surface mining operations. A major problem in excavation is the variability of material diggability, resulting in varying mechanical energy input and stress loading of shovel dipper-and-tooth assembly across the working bench. This variability impacts the shovel dipper and tooth assembly in hard formations. In addition, the geometrical constraints within the working environment impose production limitations resulting in low production efficiency and high operating costs. A potential solution to the above problems is the deployment of an intelligent shovel excavation (ISE) technology, with real-time formation identification, recording and knowledge transmission capabilities. This paper advances the ISE technology by developing dynamic models of the cable shovel using the Newton–Euler techniques. The models include the main factors that influence shovel performance including the effect of both linear and angular motions of dipper handle and dipper. A path trajectory is modeled to demonstrate the dynamic velocity and acceleration profiles. Numerical examples show that the critical performance variables include geometrical and physical properties of the dipper and dipper handle, digging strategies and formation properties. The kinematic results show that the critical phase occurs between 1.5 and 2.0 s of a 3-s excavation cycle with occurrence of maximum kinematic effects. The dynamic results also show a similar trend with maximum dynamic effects between 1.5 and 2.0 s. The results also show that the maximum resistive force occurs at 1.625 s within the excavation cycle. At this point the maximum breakout force of the equipment is reached and any increase in the resistive load will require further fragmentation. The results provide appropriate information for excavation planning and execution. These models form the basis for developing dynamic shovel simulators for the ISE technology.

Ergonomic evaluation of the effects of handle types on garden tools

The objective of this study was to evaluate quantitatively the effects of handle types of garden tools on ergonomic effectiveness, user satisfaction in terms of work performance, and subjective judgment of tactile feel and control. Shoveling performance, hand grip force and electromyography (EMG), task workload, and subjective ratings of perceived exertion were measured while using three types of garden tasks/tools (shovel, rake, and hoe) with three different handle types: a conventional wood handle and two more fiberglass handle. The most effective measure for shovels was the relative efficiency of shovel performance, that is, shovel performance divided by task workload. A hollow fiberglass handle was 12% more efficient than either a wood or solid fiberglass handle. The grip force and EMG analyses showed a similar effect, with a solid or hollow fiberglass handle requiring significantly less effort than a wood handle. Subjective ratings of the perceived exertion were also lowest for a hollow fiberglass handle. A hollow fiberglass handle showed better physiological efficiency and better subjective acceptability for comfort, tactile feel, and decreased slipperiness Relevance to industry This research presents a systematic approach to the ergonomic evaluation of new materials on improved work efficiency and user satisfaction. This quantitative examination of grip force, muscular effort, and worker's subjective ratings can be applied to the ergonomic evaluation of other newly developed product.

Integrated drill and shovel performance monitoring towards blast optimization : Hendricks, C; Peck, J; Scoble, M Proc 3rd International Symposium on Rock Fragmentation by Blasting, Brisbane, 26–31 Aug 1990P9–20. Publ Parkville: AusIMM, 1990

Integrated drill and shovel performance monitoring towards blast optimization : Hendricks, C; Peck, J; Scoble, M Proc 3rd International Symposium on Rock Fragmentation by Blasting, Brisbane, 26–31 Aug 1990P9–20. Publ Parkville: AusIMM, 1990

Assessment of blasting efficiency by seismic surveys and rope shovel performance monitoring: a case study : Pasamehmetoglu, A G; Karpuz, C; Muftuoglu, Y Int J Surf MinV5, N2, 1991, P89–93

Assessment of blasting efficiency by seismic surveys and rope shovel performance monitoring: a case study : Pasamehmetoglu, A G; Karpuz, C; Muftuoglu, Y Int J Surf MinV5, N2, 1991, P89–93

Assessment of blasting efficiency by seismic surveys and rope shovel performance monitoring: A case study

ABSTRACT In this paper, diggability assessment studies for an electrical rope shovel undertaken in a producing surface lignite mine is presented. For this purpose, a test bench is selected and shovel performance monitoring together with various surveys were carried out on this bench. Manual stopwatch surveys, recording of peak and mean power consumption of the shovel were made before and after blasting. Mass and material properties of the overburden strata were defined, seismic surveys were conducted to measure in-situ P-wave velocities before and after blasting. Bock Quality Indexes were established during blasthole drilling in order to correlated with any local variation in the overburden strata. The accumulated data was analysed in order to examine the efficiency of blasting and its likely effect on the rope shovel performance in terms of production capacity and power consumption. Furthermore a cost analysis is made in order to demonstrate the differentiation of unit handling costs between direct diggi...