Discusses an ongoing research work which attempts to formulate, develop and test mining equipment reliability assessment models based on genetic algorithms. Genetic algorithms are powerful and broadly applicable stochastic search techniques based on the principles of natural selection, heredity and genetics. The reason for selecting genetic algorithms is the fact that the reliability of mining equipment changes over time due to its dependence upon several covariates/factors (e.g. equipment age, the operating environment, number and quality of repairs). These factors combine to create a complex impact on an equipment’s reliability function. Gives an example of the application of genetic algorithms to capture the impact of these factors on time between failures of a piece of mining equipment.
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1 December 2001
Conceptual Paper|
December 01 2001
Genetic algorithms for reliability assessment of mining equipment Available to Purchase
Nick Vagenas;
Nick Vagenas
Laurentian University Mining Automation Laboratory (LUMAL), Sudbury, Ontario, Canada
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Tony Nuziale
Tony Nuziale
Laurentian University Mining Automation Laboratory (LUMAL), Sudbury, Ontario, Canada
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Publisher: Emerald Publishing
Online ISSN: 1758-7832
Print ISSN: 1355-2511
© MCB UP Limited
2001
Journal of Quality in Maintenance Engineering (2001) 7 (4): 302–311.
Citation
Vagenas N, Nuziale T (2001), "Genetic algorithms for reliability assessment of mining equipment". Journal of Quality in Maintenance Engineering, Vol. 7 No. 4 pp. 302–311, doi: https://doi.org/10.1108/13552510110407087
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