TITLE:
Maintainability Analysis Software of Mine’s Hoist System Based on Genetic Algorithms for Data Collection Periods of Three and Six Months
AUTHORS:
Chao Xu, Nick Vayenas
KEYWORDS:
Maintainability, Genetic Algorithms, Mine’s Hoist System, GenRel
JOURNAL NAME:
Open Access Library Journal,
Vol.2 No.11,
November
13,
2015
ABSTRACT:
Equipment failures and associated maintenance have an impact on the
profitability of mines. Implementing maintenance at suitable time intervals can
save money and improve the reliability and maintainability of mining equipment.
This paper discusses aspects of maintainability prediction for mining
machinery. For this purpose, a software tool, called GenRel, is developed. In
GenRel, it is assumed that failures of mining equipment caused by an array of
factors follow the biological evolution process. GenRel then simulates the
failure occurrences during a time period of interest using Genetic Algorithms
(GAs) coupled with a statistical methodology. Two case studies on maintainability
analysis and prediction of a mine’s hoist system in two different time
intervals, three months and six months are discussed. The data are collected
from a typical underground mine in the Sudbury area in Ontario, Canada. In each
case study, a statistical test is carried out to examine the similarity between
the predicted data set and the real-life data set in the same time period. The
objectives include an assessment of the applicability of GenRel using real-life
data and an investigation of the relationship between data size and prediction
results. Discrete and continuous probability distribution functions are applied
to the input data.