The flow of information and consequently the decision making along the chain of mining from exploration to beneficiation typically occurs in a discontin- uous fashion over long time spans. In addition, due to the uncertain nature of the knowledge about the deposit and its inherent spatial distribution of material char- acteristics actual production performance in terms of produced ore grades and quantity and extraction process efficiency often deviate from expectations. Reconciliation exercises to adjust mineral reserve models and planning assumptions are performed with timely lags of weeks, months or even years. With the devel- opment of modern Information and Communication Technology over the last decade, literally a flood of data about different aspects of the production process is available in a real-time manner. For example, sensor technology enables online characterisation of geochemical, mineralogical and physical material characteristics on conveyor belts or at working faces. The ability to utilise the value of this additional information and feed it back into reserve block models and planning assumptions opens up new opportunities to continuously control the decisions made in production planning to increase resource recovery and process efficiency. This leads to a change in paradigm from a discontinuous to a near real-time reserve reconciliation and model updating, which calls for suitable modelling and optimi- sation methodologies to quantify prior knowledge in the reserve model, to process and integrate information from different sensor-sources and accuracy, back prop- agate the gain in information into reserve models and efficiently optimise opera- tional decisions real-time. This contribution introduces the concept of an integrated closed-loop framework for Real-Time Reserve management (RTRM) incorporating

Original languageEnglish
Title of host publicationAdvances in Applied Strategic Mine Planning
PublisherSpringer International Publishing
Pages725-744
Number of pages20
ISBN (Electronic)9783319693200
ISBN (Print)9783319693194
DOIs
Publication statusPublished - 17 Jan 2018

ID: 44942591