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
| Identifer | oai:union.ndltd.org:UBC/oai:circle.library.ubc.ca:2429/2741 |
| Date | 05 1900 |
| Creators | Sharma, Gaurav Kumar |
| Publisher | University of British Columbia |
| Source Sets | University of British Columbia |
| Language | English |
| Detected Language | English |
| Type | Text, Thesis/Dissertation |
| Format | 2044838 bytes, application/pdf |
| Rights | Attribution-NonCommercial-NoDerivatives 4.0 International, http://creativecommons.org/licenses/by-nc-nd/4.0/ |
Page generated in 0.0016 seconds