Application scenarios of artificial intelligence AI in the mining industry chain include but are not limited to:
1. Automated exploration and prospecting: AI can automate geological exploration and prospecting activities by analyzing large amounts of sensor data and acoustic images. This can improve exploration and mining efficiency and reduce mining costs.
2. Intelligent mine planning: AI can analyze a large amount of geological data, comprehensively analyze and judge the topography, geological body, mineral distribution and other information of the mining area, intelligently carry out mine planning, and improve mining efficiency.
3. Intelligent mine operation system: AI can realize real-time monitoring and control of the mine operation process through multi-dimensional data analysis and intelligent early warning system, and can automatically adjust the operation status of excavators, transport vehicles and other equipment to ensure the efficiency, safety and sustainability of the production process.
4. Mining process optimization: AI can optimize the process of ore mining and crushing, realize automatic control of equipment and processes, improve mining efficiency and ore quality, and reduce environmental pollution.
5. Intelligent mining management: AI can centrally monitor and analyze the production and logistics data of mines, analyze problems, and provide optimization suggestions to improve the informatization, intelligence and efficiency of mine management.
6. Automated mining robots: AI can develop mining robots with autonomous decision-making and execution capabilities through technologies such as self-learning and autonomous planning, so as to realize unmanned mining and improve production efficiency and safety.
7. Intelligent maintenance and repair: AI can warn of maintenance problems in advance through real-time monitoring of equipment, automatically plan repair plans and automatically assign maintenance tasks, and reduce the time and cost of equipment failure.
8. Mineral quality analysis: AI can scan the surface of the ore, identify the ore species, and perform fine analysis of the mineral composition in the ore stone, so as to improve the accuracy and detection efficiency of mineral quality.
9. Data-based mining process: AI can model the mining process of the mine data, and statistically derive data models such as key performance indicators and process influencing factors to help good mineral production.
10. Ambitious energy plans: AI can prioritize energy plans by identifying the multiple uses and characteristics of minerals to ensure efficient coordination between the mine's production and energy sectors and improve energy efficiency.
11. Resource price forecasting: AI can help mining companies accurately predict resource price fluctuations and reasonably formulate procurement plans and sales strategies through monitoring and analysis of global economic conditions, market demand, resource supply and global political situation.
12. Intelligent control of mining tank: use AI technology to optimize the operation of mining tank, improve production capacity through intelligent management, optimize each production link, and make the operation of the mine tank more stable and balanced.
13. Safety monitoring and prevention system: AI can be integrated with dangerous goods employee management personnel to maintain high-quality industrial hygiene standards and ensure that all workplaces are harmless to human health and safety.
14. Environmental protection: AI can analyze and process a large amount of environmental monitoring data, analyze and monitor the water quality, air, soil and vegetation of the mine environment, monitor the discharge of pollutants, and reduce the damage and pollution to the natural environment. At the same time, AI technology can also be used to automate environmental protection work such as garbage classification, wastewater treatment, energy conservation and emission reduction.
15. Platform mining services: AI technology is used to enhance the interaction and collaboration of the mining ecosystem, so that mining participants can get fast and more accurate information feedback, provide customizable services, and ensure the matching of market demand with demands and mining resources.