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Bayesian statistics and production reliability assessments for mining operations

This thesis presents a novel application of structural reliability concepts to assess the
reliability of mining operations. “Limit-states” are defined to obtain the probability that the
total productivity — measured in production time or economic gain — exceeds user-selected
thresholds. Focus is on the impact of equipment downtime and other non-operating instances
on the productivity and the economic costs of the operation. A comprehensive set of data
gathered at a real-world mining facility is utilized to calibrate the probabilistic models. In
particular, the utilization of Bayesian inference facilitates the inclusion of data — and
updating of the production probabilities — as they become available. The thesis includes a
detailed description of the Bayesian approach, as well as the limit-state-based reliability
methodology. A comprehensive numerical example demonstrates the methodology and the
usefulness of the probabilistic results. / Applied Science, Faculty of / Civil Engineering, Department of / Graduate

Identiferoai:union.ndltd.org:UBC/oai:circle.library.ubc.ca:2429/2741
Date05 1900
CreatorsSharma, Gaurav Kumar
PublisherUniversity of British Columbia
Source SetsUniversity of British Columbia
LanguageEnglish
Detected LanguageEnglish
TypeText, Thesis/Dissertation
Format2044838 bytes, application/pdf
RightsAttribution-NonCommercial-NoDerivatives 4.0 International, http://creativecommons.org/licenses/by-nc-nd/4.0/

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