Real-time resource model updating in continuous mining environment utilizing online sensor data

Cansin Yüksel

Research output: ThesisDissertation (TU Delft)

314 Downloads (Pure)

Abstract

In mining, modelling of the deposit geology is the basis for many actions to be taken in the future, such as predictions of quality attributes, mineral resources and ore reserves, as well as mine design and long-term production planning. The essential knowledge about the raw materialproduct is based on this model-based prediction, which comes with a certaindegree of uncertainty. This uncertainty causes one of the most common problems in the mining industry, predictions on a small scale such as a train load or daily production are exhibiting strong deviations from reality.Some of the most important challenges faced by the lignite mining industry are impurities located in the lignite deposit. Most of the times, these high ash values cannot be captured completely by exploration data and in the predicted deposit models. This lack of information affects the operational process.
Original languageEnglish
Awarding Institution
  • Delft University of Technology
Supervisors/Advisors
  • Jansen, J.D., Supervisor
  • Benndorf, Jörg, Supervisor
  • Buxton, M.W.N., Advisor
Award date13 Dec 2017
Print ISBNs978-94-6233-803-6
DOIs
Publication statusPublished - 2017

Keywords

  • mining
  • online sensor data

Fingerprint Dive into the research topics of 'Real-time resource model updating in continuous mining environment utilizing online sensor data'. Together they form a unique fingerprint.

Cite this