Using AI to automatically generate mining algorithms

利用AI自动生成挖矿算法

• 批准号: 544678-2019
• 负责人: Rogers, Kevin
• 金额: $ 10.93万
• 依托单位: Saskatchewan Polytechnic
• 依托单位国家: 加拿大
• 项目类别: Applied Research and Development Grants - Level 3
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=721003
• 关键词: Using; AI; automatically; generate; mining

Hard-rock mining of uranium in Canada's north is challenging and often difficult. Operating risk exposures are heightened when mining in high-grade uranium ore bodies that are exposed to possible flooding from water above the mine. To succeed in this environment Cameco has successfully mechanized their operations and relies on Jet Boring technology. This proposed project is planned to advance the visibility and automation systems for Jet Boring by: 1) creating large volumes of data created by ongoing measurement of the process; 2) collecting, analyzing, and synthesizing that data in order to form conclusions; and 3) confirming the effectiveness of using those conclusions to inform, control and direct operational decisions and automation of the mechanized Jet Boring systems. At this early stage, proof of concept level work will identify further opportunities that can point to or suggest a roadmap for further automation and optimization possibilities within mining.

加拿大北部铀的硬岩开采具有挑战性，而且通常很困难。当在矿山上方的水中暴露于可能洪水的高级铀矿体中采矿时，运营风险暴露会增加。为了在这种环境中取得成功，Cameco成功地将其运营机械化，并依赖于Jet Boring Technology。该提出的项目计划通过以下方式推进喷气式钻机的可见性和自动化系统：1）创建通过持续测量过程创建的大量数据； 2）收集，分析和综合该数据以形成结论； 3）确认使用这些结论来告知，控制和直接操作决策以及机械化喷气机系统的自动化的有效性。在这个早期阶段，概念级别的工作将确定可能指向或建议采矿内进一步自动化和优化可能性的路线图的进一步机会。