Print Email Facebook Twitter The use of sensor derived data in optimization along the Mine-Value-Chain Title The use of sensor derived data in optimization along the Mine-Value-Chain Author Buxton, M.W.N. Benndorf, J. Faculty Civil Engineering and Geosciences Department Geoscience & Engineering Date 2013-12-31 Abstract 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 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. Subject sensor based material discriminationreal time optimization To reference this document use: http://resolver.tudelft.nl/uuid:36b7c421-118b-41fe-989c-35710b8999b5 Publisher Papierflieger ISBN 978-3-86948-294-1 Source 15th International ISM congress, Aachen (Germany) 16-20 Sept., 2013 Part of collection Institutional Repository Document type conference paper Rights (c) 2013 The Authors Files PDF 296116.pdf 2.18 MB Close viewer /islandora/object/uuid:36b7c421-118b-41fe-989c-35710b8999b5/datastream/OBJ/view