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

Doctoral thesis (2017)

Authors

C. Yuksel-Pelk Resource Engineering - CEG
Research Group
Resource Engineering (CEG) (TU Delft)
Copyright: © 2017 C. Yuksel-Pelk
DOI: https://doi.org/10.4233/uuid:1572a346-95c9-43a5-bf81-81d1fbfde2e9
Mining Online sensor data
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Published Date

2017

Language

English

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Faculty

Civil Engineering & Geosciences

Department

Geoscience and Engineering

Research Group

Resource Engineering

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.