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.
Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:BVAU./2741 |
Date | 05 1900 |
Creators | Sharma, Gaurav Kumar |
Publisher | University of British Columbia |
Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
Language | English |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Format | 2044838 bytes, application/pdf |
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