At present, data exchange in China’s digital mine construction process is still based on paper media or electronic documents. The problems of “information islands,” “information versions,” “information faults” and “information preservation” are serious. There are many problems associated with across time and space and multidisciplinary collaborations, blocked business processes and unclear job responsibilities. These problems have seriously hindered the construction of China’s digital mine, thus restricting the safe, efficient production and sustainable development of China’s mining enterprises. Therefore, this paper proposes the concept, connotation, characteristics, architecture and technical requirements of the mining technology collaboration platform and uses it to guide the research and development and implementation of the mining technology collaboration platform of Fujian Makeng Mining Co., Ltd. The results show that the mining technology collaboration platform can solve the information and management problems existing in China’s digital mine construction and realize the centralized storage, interoperability and high sharing of all data, the integration of all involved business, business software and its participants, the clarification of responsibilities and its input and output data of each post and standardization and automation of business process. Therefore, it improves the ability to collaborate across time and space and multidisciplinary among participants, departments and professional posts, ensures high-speed flow of business processes and also improves the working efficiency and quality of mining enterprises and significantly reduces the time for business processing and business process flow and reduces production costs.

In this paper, according to the analysis of optimum circuits, we present an efficient ventilation network solution based on minimum independent closed loops. Our main contribution is optimizing the circuit dividing strategy to improve the iteration convergence and the efficiency of a single iteration. In contrast to a traditional circuit, a minimum closed loop may contain one or more co-tree branches but fewer high-resistance branches and fan branches. It is helpful in solving the problem of divergence or slow convergence for complex ventilation networks. Moreover, we analyze the dividing rules of closed loops and improve the dividing algorithm of minimum independent closed loops. Compared with the traditional Hardy Cross iteration method, the improved solution method has better iteration convergence and computation efficiency. The experimental results of real-world mine ventilation networks show that the improved solution method converges rapidly within a small number of iterations. We also investigate the influence of network complexity, iterative precision, and initial airflow on the iteration convergence.

Equipment failure is a common problem in mining operations, resulting in significant delays and reductions in production efficiency. To address this problem, this paper proposes a dynamic scheduling model for underground metal mines under equipment failure conditions. The model aims to minimize the impact of equipment failures on production operations while avoiding extensive equipment changes. A case study of the southeastern mining area of the Chambishi Copper Mine is presented to demonstrate the effectiveness of the proposed model. The initial plan was generated using the multi-equipment task assignment model for the horizontal stripe pre-cut mining method. After equipment breakdown, the proposed model was used to reschedule the initial plan. Then, a comparative analysis was carried out. The results show that the proposed model effectively reduces the impact of equipment failures on production operations and improves overall mining execution at a low management cost. In general, the proposed model can assist schedulers in allocating equipment, coping with the disturbing effects of equipment failure, and improving mine production efficiency.

To investigate the influence of different burial conditions on the seepage characteristics of loose sandstone in the leaching mining of sandstone uranium ore, this study applied different ground pressures and water pressures to rock samples at different burial depths to alter the rock's seepage characteristics. The permeability, pore distribution, and particle distribution characteristic parameters were determined, and the results showed that at the same burial depth, ground pressure had a greater effect on the reduction in permeability than water pressure. The patterns and mechanisms are as follows: under the influence of ground pressure, increasing the burial depth compresses the pores in the rock samples, decreases the proportion of effective permeable pores, and causes particle fragmentation, which blocks pore channels, resulting in a decrease in permeability. Under the influence of water pressure, increasing the burial depth expands the pores but also causes hard clay particles to decompose and block pore channels. As the burial depth increases, the particles eventually decompose completely, and the permeability initially decreases and then increases. In this experiment, the relationships between permeability and the proportion of pores larger than 0.15 μm and the proportion of particles smaller than 59 μm were found to be the most significant.

The continuity and homogeneity of sandstone uranium deposits are inherent characteristics that affect in situ leaching performance indexes and have important guiding effects on the optimization of mining design. In this work, we propose a spatial information entropy calculation method based on a convex hull search strategy to quantitatively evaluate the geological characteristics of uranium deposits. We use the 3-D block model of sandstone-hosted uranium deposits as hard data. First, we use the Alpha-Shapes algorithm to calculate the convex hull of the space area where various types of unit blocks are located. Second, we formulate a suitable multi-point configuration based on the convex hull size. Then, we use the multi-point density function. Scanning the convex hull point cloud establishes a probability density function to calculate the local information entropy of various sub-regions. Finally, the local spatial information entropy is aggregated using addition and multiplication to obtain the joint spatial information entropy of the entire evaluation area. A series of parameter sensitivity and performance analysis experiments prove the stability of the method and the accuracy of the quantitative and homogeneous evaluations of the complex geological conditions. In order to solve the problem of the difference between the designed production capacity and actual production capacity of a uranium deposit, we use a new method to evaluate the homogeneity and continuity of the lithology and grade of the deposit. The new method and evaluation conclusions can be used for the automation and understanding of future engineering optimization processes.

This paper proposes a multi-equipment task assignment model for the horizontal stripe pre-cut mining method to address the problem of cooperative scheduling operation of multi-equipment in underground metal mines under complex constraints. The model is constructed with multiple objectives, including operation time, operational efficiency, equipment utilization rate, and ore grade fluctuation by considering the constraints of time, space, equipment, and processes. The NSGA-III algorithm is used to obtain the solution. The effectiveness of the algorithm is tested based on the actual data from the Chambishi Copper Mine. The results show that the average equipment utilization rate is 51.25%, and the average ore output efficiency is 278.71 tons/hour. The NSGA-III algorithm can quickly generate the optimal multi-equipment task assignment solution. The solution reduces the interference of manual experience and theoretically improves the actual operation of the mine.