A new stope optimization for underground mining operations

加拿大是一个资源丰富的国家，以地下矿山著称。中国的金属回收 地下矿山由于贫化突出，开采成本较高，通常开采深度较低。自.以来 生产决策是由岩石力学决定的，也没有大的回旋余地 在整个采矿作业中进行修改。因此，规划阶段对企业的成功有着至关重要的作用 制作。在过去的几年里，全球矿业经历了价格下跌，这导致了 这是一个额外的挑战，使地下采矿业务处于利润率的边缘。一 应对这些挑战的方法是通过优化生产布局和 在不违反岩土工程、洞口稳定性、回填养护、稀释、 容量和等级要求。多亏了新的运筹学和计算机技术，生产 布局和排序问题可以通过新兴的技术重新制定和解决。这个问题可能是 表示为适合生产方法和相关约束的线性/非线性优化问题。 为了生成适用的优化模型，需要了解岩土工程之间的相互作用 特性、钻探/爆破实践、回填养护、稀释和回收。这项研究旨在 (1)量化输入到模型中的这些相互作用，以及(2)开发如下优化模型 将生成最佳提取配置。全球黄金领军企业之一Goldcorp 矿业，一直关注改善他们的地下采矿作业，并表示有兴趣 与麦吉尔研究人员合作，开发生产布局和排序的优化模型。 这一创新研究将使Goldcorp在矿业领域变得更强大和更具竞争力。这 Engage Support还将帮助Goldcorp与 申请者的研究团队，其中将介绍高效和多产的矿山优化实践 加拿大采矿业。

Canada is a resource-endowed country and generally known with underground mines. Metal recoveries in underground mines are usually low due to prominent dilution and the operation costs are high. Since production decisions are governed by rock mechanics, there is also no big maneuvering room to make major modifications throughout mining operations. Therefore, the planning stage has a vital role for a successful production. Over the last few years, global mineral industries have experienced with falling prices, which cause an extra challenge in such a way as to bring underground mining operations on the brink of profit margin. One way to respond to these challenges is to rationalize the operations through optimizing production layouts and determining sequences without the violation of geo-technical, stability of openings, backfill curing, dilution, capacity and grade requirements. Thanks to new operation research and computer technologies, production layout and sequencing problem can be re-formulated and solved by emerging techniques. This problem can be expressed as linear/non-linear optimization problems suiting the production method and associated constraints. To generate applicable optimization models, it is required to understand the interactions among geo-technical characterization, drilling/blasting practices, backfill curing, dilution and recovery. This research addresses to (1) quantify these interactions, which are inputted to the models, and (2) develop the optimization models such that the best extraction configurations will be generated. Goldcorp, one of global leader companies in gold mining, always concerns about improving their underground mining operations and expressed an interest to collaborate with McGill researchers to develop the optimization models for production layout and sequencing. This innovative research will make Goldcorp more powerful and competitive in mineral industries. This ENGAGE support will also assist Goldcorp in establishing long-term research collaboration with the applicant's research team in which efficient and productive mine optimization practices will be introduced to Canadian mining industry.