Design Optimization Methodologies for Multi-stage Samplers in Mining Applications

在采矿业，可靠的矿物生产会计对健全的公司治理至关重要，特别是因为金属会计系统产生的数字直接输入采矿公司的财务账户。在许多情况下，金属核算需要精确测量浆料流中的金属含量，浆料流是在许多矿物加工厂中发现的液体介质（例如水）中的固体颗粒的流体混合物，作为散装运输和处理固体颗粒（例如提取的矿物）的方便方式。该研究项目的目标是开发方法和算法来优化泥浆采样系统的设计，以提高其精度并减少采样偏差，从而提供更准确和更具成本效益的泥浆流中矿物含量的核算。这些发展对采矿业的潜在影响是惊人的，因为抽样准确性的提高只是百分之一点几。 系统可以影响数百万美元的收入。该项目的成功完成还将有助于加拿大公司发展和/或保持其在全球采矿服务和设备市场上的领导地位。

In the mining industry, reliable accounting of mineral production is essential to sound corporate governance, particularly as the figures generated by metal accounting systems feed directly into the financial accounts of mining companies. In many instances, metal accounting requires accurate measurement of metal content in slurry flows, which are fluid mixtures of solid particles in a liquid medium (e.g. water) found in many mineral processing plants as a convenient way of transporting and handling solid particles (e.g. extracted minerals) in bulk. The goal of this research project is to develop methods and algorithms to optimize the design of slurry sampling systems to improve their precision and reduce sampling bias, thus providing more accurate and cost-effective accounting of mineral content in slurry flows. The potential impact of these developments on the mining industry is astounding, as just a fraction of a percent improvement in the accuracy of the sampling system can impact millions of dollars in revenues. Successful completion of the project would also help Canadian firms to develop and/or maintain their leadership in the global market for mining services and equipment.