Search Results (4)

The electric cable shovel (ECS) is one of the core pieces of equipment used in open-pit mining, and the prediction of its excavating resistance is the basis and focus of optimization design, such as excavation trajectory planning and structure optimization of the ECS. Aiming to predict the excavating resistance of an ECS, a computer simulation method for the excavating resistance based on EDEM-RecurDyn bidirectional coupling simulation is proposed herein. Taking the China-made WK series ECS as the research object, a 1/30 scale model of the ECS was set up, a prototype model test bench of the ECS was built, and the kinematics solution and force analysis of the excavating process were carried out. According to the actual excavation conditions and excavating process of the ECS, a discrete element model of the material stack and a multibody dynamics model of the ECS prototype were established. The EDEM-RecurDyn bidirectional coupling simulation of the excavating process were realized using interface technology, and the excavating resistance levels under different speed combinations and different material repose angles were simulated and analyzed. In order to verify the accuracy of the simulation results, the feasibility and reliability of the EDEM-RecurDyn bidirectional coupling simulation were verified by physical experiments. The results show that the simulated excavating resistance is basically consistent with the excavating resistance measured in the experiment in terms of peak value and change trend, which verifies the feasibility and reliability of the EDEM-RecurDyn bidirectional coupling simulation to study the excavating resistance of an ECS. Full article

Forests in Korea are mainly located in steep mountainous areas, where small-shovel-based extraction technology is widely used, with the level of mechanization undoubtedly low due to financial limitations. On this steep terrain, a better approach may be to use cable yarders, which can offer high revenues through cable-based extraction. Therefore, improving the efficiency of cable yarding activities in good-quality timber forests is necessary. The main objectives of this study were to (1) evaluate the productivity and cost of a cable yarder operation for tree-length clearcut treatment of a Larix kaempferi (Lamb.) Carr. stand and (2) compare the productivity efficiency of two yarder (K301-4 and HAM300) types. The productivity rates of the K301-4 ranged from 10.2 to 12.5 m³/productive machine hours, with corresponding costs of US $12.6–15.4 /m³. The productivity of the HAM300 was 26% lower than that of the K301-4 for a 30% lower cycle log volume while yarding and a comparable lateral distance. This study provides insights to support production and management decisions in the forest supply chain associated with planning cable-yarding operations. Full article

As one of the most essential earth-moving equipment, cable shovels significantly influence the efficiency and economy in the open-pit mining industry. The optimal digging trajectory planning for each cycle is the base for achieving effective and energy-saving operation, especially for robotic excavation, in which case, the digging trajectory can be precisely tracked. In this paper, to serve the vision of cable shovel automation, a two-phase multi-objective genetic algorithm was established for optimal digging trajectory planning. To be more specific, the optimization took digging time and energy consumption per payload as objects with the constraints of the limitations of the driving system and geometrical conditions. The WK-55-type cable shovel was applied for the validation of the effectiveness of the multi-objective optimization method for digging trajectories. The digging performance of the WK-55 cable shovel was tested in the Anjialing mining site to establish the constraints. Besides, the digging parameters of the material were selected based on the tested data to make the optimization in line with the condition of the real digging operations. The optimization results for different digging conditions indicate that the digging time decreased from an average of $20\mathrm{s}$ to $10\mathrm{s}$ after the first phase optimization, and the energy consumption per payload reduced by $\mathrm{13.28\%}$ after the second phase optimization, which validated the effectiveness and adaptivity of the optimization algorithm established in this paper. Full article

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. Full article