Quantitative methods for sustainability analysis and integrated management of mining systems

采矿系统可持续性分析和综合管理的定量方法

• 批准号: RGPIN-2020-04605
• 负责人: Navarra, Alessandro
• 金额: $ 1.89万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=714860
• 关键词: Quantitative; methods; sustainability; analysis; integrated

Mine development projects are capital intensive and risky, and must therefore be engineered in phases. Early phases have relatively small budgets, and determine whether or not to pursue the subsequent phases that require larger budgets. This multiphase approach is essential to sustainable engineering, and is known as Front End Loading (FEL). It requires system-wide quantitative analysis of economic, social and environmental impacts, applied within every phase, and is subject to multiobjective optimization; it determines if the final design should be implemented. Furthermore, if the design is actually implemented, the quantitative analysis becomes the basis for integrated and sustainable management of the resulting mining system. The current proposal is to develop the quantitative frameworks to evaluate modern control and automation strategies, which apply geostatistical and geometallurgical modeling, for system-wide coordination of the mineral value chain. Early within a project, the system may be represented with only the principle material and energy flows, as in standard Life-Cycle Assessment, supported by static Monte Carlo simulation. The more developed models require dynamic representations, supported by discrete event simulation; they can describe unplanned events, and/or surges in material and energy inputs, as well as environmental releases. It is ultimately the dynamic surging that presents environmental risks, whenever system tolerances are approached or exceeded. Variations in the orebody, equipment, and market conditions can trigger changes in the mode of operation. The standardization of operational practices ensures that coherent instructions are sent to the various unit operations throughout the mine, in response to events and trends. Moreover, operational data is continually accumulated, which supports process optimization through machine learning. For example, a change in the rock type may require a change in the blasting pattern, as well as corresponding (machine learnt) changes in the downstream comminution parameters. Alternating operational modes are thus an integrated response to process variation. However, the available modes are limited by the equipment that is selected, and must therefore be considered early within the design process. Considering the competitive nature of the mining industry, the sustainability of mines may indeed depend on the intelligent coordination of automated technology.

矿山开发项目是资本密集型项目，风险很大，因此必须分阶段进行。早期阶段的预算相对较小，并决定是否继续进行需要更大预算的后续阶段。这种多阶段方法对于可持续工程至关重要，被称为前端加载（FEL）。它要求对经济、社会和环境影响进行全系统的定量分析，在每个阶段都要应用，并要进行多目标优化;它决定是否应该实施最终设计。此外，如果设计得到实际执行，定量分析将成为对所产生的采矿系统进行综合和可持续管理的基础。 目前的建议是制定量化框架，以评估现代控制和自动化战略，其中应用地质统计学和几何建模，以促进矿物价值链的全系统协调。在项目的早期，系统可能仅用主要的材料和能量流来表示，就像在标准的生命周期评估中一样，由静态蒙特卡罗模拟支持。较先进的模型需要动态表示，并得到离散事件模拟的支持;它们可以描述意外事件和/或材料和能源投入的激增以及环境释放。最终，当系统公差接近或超过时，动态波动会带来环境风险。 矿体、设备和市场条件的变化可能引发经营模式的变化。操作实践的标准化确保了针对事件和趋势向整个矿山的各个单元操作发送一致的指示。此外，运营数据不断积累，通过机器学习支持流程优化。例如，岩石类型的变化可能需要爆破模式的变化，以及下游粉碎参数的相应（机器学习）变化。因此，交替的操作模式是对过程变化的综合响应。然而，可用的模式受到所选设备的限制，因此必须在设计过程中尽早考虑。考虑到采矿业的竞争性质，矿山的可持续性可能确实取决于自动化技术的智能协调。