Automation and optimization of drilling operations in open-pit mines

该研究计划提出使用分析方法（机器学习，海量数据和优化）来自动化露天矿中用于钻爆孔的钻头的运动。该计划是与派克技术咨询公司，安赛乐米塔尔矿业加拿大公司，Teck Resources Ltd. 其目标是使用由Peck Tech开发并安装在钻机上的各种传感器收集的数据来自动化和优化钻井作业，并确定这些新信息如何帮助本地更新地质模型。更新后的地质模型将用于重新优化钻孔和爆破模式。最后，将使用优化算法来确定最佳钻孔顺序以及钻头应如何协作以在相同的钻孔模式上执行工作。Peck Tech传感器已经安装在ArcelorMittal Mining Canada G.P.和Teck Resources Ltd.拥有的露天矿的钻机上。 这些研究项目将由五名博士生和一名博士后进行，并由来自三个工业合作伙伴的六名教授和九名专业人士组成的团队进行监督。对这些高技能分析人员的培训需求很大，对于寻求向矿山数字化过渡的采矿业至关重要。

This research program proposes the use of analytical methods (machine learning, massive data and optimization) to automate the movements of drills used in open pit mines to drill blast holes. This program is done jointly with Peck Tech Consulting, ArcelorMittal Mining Canada G.P., and Teck Resources Ltd. The goal is to use the data collected by the various sensors developed and installed on the drills by Peck Tech to automate and optimize drilling operations, and to determine how this new information could help to locally update the geological model. The updated geological model will then be used to re-optimize the drilling and blasting patterns. Finally, optimization algorithms will be used to determine the optimal drilling sequence and how the drills should cooperate to perform the work on the same drill pattern. Peck Tech sensors are already installed on drills that are operating in open pit mines owned by ArcelorMittal Mining Canada G.P. and Teck Resources Ltd. These research projects will be carried out by five doctoral students and one postdoctoral fellow, and supervised by a team of six professors and nine professionals from the three industrial partners. The training of this highly skilled analytical staff is in high demand and is essential for the mining industry that seeks to make the transition to the digitization of their mines.