Data Analytics for Ore Blending Schedules

采矿业是加拿大的主要产业之一，为加拿大国内生产总值(GDP)贡献了560亿美元，占2015年加拿大商品出口额的19%。矿业公司面临的一个关键战略和运营挑战是制定矿石混合计划，即在公司向市场提供的最终产品中加入矿石混合计划。虽然更高质量的矿石混合物会导致产品价格上涨，但混合是延长矿山寿命和制定具有成本效益的采矿生产计划的关键过程。尽管如此，大多数加拿大公司仍然手动或使用不太理想的方法制定矿石混合计划。在这个项目中，申请者将与该矿区的加拿大咨询公司Magemi Mining，Inc.合作，开发新的数据分析方法，以设计动态的长期矿石混合时间表。该项目扩展了该地区最先进的优化技术，并将由Magemi矿业公司直接应用于其客户。

Mining is one of Canada's primary industries, contributing $56 billion to Canada's Gross Domestic Product(GDP) and responsible for 19% of the value of Canadian goods exports in 2015. A key strategic andoperational challenge faced by mining companies is the creation of ore blending schedules, that is, which oresto combine in the final products that the company offers to the market. While higher-quality ore mixtures leadto products with elevated prices, blending is a crucial process for extending the life of the mine and ingenerating cost-effective mining-production plans. Nonetheless, the majority of Canadian companies stillcreate their ore blending schedules manually or using suboptimal methods. In this project, the applicant willpartner with Magemi Mining, Inc., a Canadian consulting firm in the mining area, to develop newdata-analytics methodologies for the design of dynamic long-term ore blending schedules. The project extendsthe state-of-the-art optimization technologies in the area and will be directly applied by Magemi Mining, Inc. toits clients.