THE USE OF SENSOR DERIVED DATA IN REAL TIME MINE OPTIMIZATION: A PRELIMINARY OVERVIEW AND ASSESSMENT OF TECHNO-ECONOMIC SIGNIFICANCE

摘要

Sensor derived data can add value across the mining operating chain ranging from resource definition, extraction, pre - concentration, mineral process monitoring and assessment of product quality. Most documented studies on the use of sensors in mining focus on specific technologies for specific applications. These studies do not take into account different aims, objectives and operating conditions at different steps in the value chain. The first part of this contribution assesses key physical performance and discriminatory requirements of sensors applied in each portion of the mining value chain. The second part proposes a framework of methods for quantifying the value added by additional sensor information. Integrating the sensor based technology and the economic value quantification allows for both, designing an economically optimal sensor monitoring network along the whole mining value chain and optimizing efficiencies. Illustrative studies demonstrate the significant economic benefits, in particular in reduction of exploration expenditures, increase in extraction efficiencies, increase in ore product quality and improvement of processing efficiencies.