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.
Cite this paper
Xu, C. and Vayenas, N. (2015). Maintainability Analysis Software of Mine’s Hoist System Based on Genetic Algorithms for Data Collection Periods of Three and Six Months. Open Access Library Journal, 2, e2022. doi: http://dx.doi.org/10.4236/oalib.1102022.
(1990)
In: Michalewicz, Z., Ed., Proceedings of the 5th
International Conference on Statistical Scientific Databases: Lecture Notes in Computer Science, Vol. 420, Springer-Verlag, New York.
Srivastava, P.R. and
Kim, T. (2009) Application of Genetic Algorithm
in Software Testing. International Journal of Software Engineering and Its Applications, 3.
Shi, L., Da, L. and Fu, H. (2005) An Application of Genetic
Algorithm in Engineering Optimization. Current Trends in High Performance Computing and Its Applications,
431-435.
McCall, J. (2005) Genetic Algorithms for Modelling
and Optimization. Journal of Computational and Applied Mathematics, 184, 205-222. http://dx.doi.org/10.1016/j.cam.2004.07.034
Aytug, H., Khouja, M. and Vergara, F.E. (2003) Use of Genetic Algorithms to
Solve Production and Operations Management Problems: A Review. International Journal of Production Research,
41, 3955-4009. http://dx.doi.org/10.1080/00207540310001626319
Dawid, H. and Kopel, M.
(1998) On Economic
Applications of the Genetic Algorithm: A Model of the Cobweb Type. Journal of Evolutionary Economics, 8, 297-315. http://dx.doi.org/10.1007/s001910050066
Proudlove, N.C., Vadera, S. and Kobbacy, K.A.H.
(1998) Intelligent
Management Systems in Operations: A Review. Journal
of the Operational Research Society, 49, 682-699. http://dx.doi.org/10.1057/palgrave.jors.2600519
Clement, S.R. and Vayenas, N.
(1994) Use of
Genetic Algorithms in a Mining Problem. International
Journal of Mining, Reclamation and
Environment, 8, 131-136. http://dx.doi.org/10.1080/09208119408964774
Ataei, M. and Osanloo, M. (2003) Using a Combination of Genetic
Algorithm and the Grid Search Method to Determine Optimum Cutoff Grades of
Multiple Metal Deposits. International
Journal of Mining, Reclamation and
Environment, 18, 60-78.
Pendharkar, P.C. and Rodger, J.A.
(2000) Nonlinear
Programming and Genetic Search Application for Production Scheduling in Coal
Mines. Annals of Operations Research,
95, 251-267. http://dx.doi.org/10.1023/A:1018958209290
He, M., Wei, J., Lu, X. and
Huang, B. The Genetic
Algorithm for Truck Dispatching Problems in Surface Mine. Information Technology Journal, 9, 710-714.
Vayenas, N. and
Nuziale, T. (2001) Genetic Algorithms for Reliability Assessment of Mining
Equipment. Journal of Quality in
Maintenance Engineering, 7, 302-311. http://dx.doi.org/10.1108/13552510110407087
Wu, X. (2009) Reliability Assessment of Mobile
Mining Equipment Using Genetic Algorithms Combined with Maintenance Analysis: A
Case Study of a Fleet of Load-Haul-Dump (LHD) Vehicles. Master’s Thesis, Laurentian University,
Sudbury.
Vayenas, N.,
Runciman, N. and Clement, S.R. (1997) A Methodology for Maintenance Analysis of Mining
Equipment. International Journal of
Surface Mining, Reclamation and
Environment, 11, 33-40. http://dx.doi.org/10.1080/09208119708944053
Xu, C. (2014) Application of GenRel for Maintainability
Analysis of Underground Mining Equipment: Based on Case Studies of Two Hoist
Systems. Master’s Thesis, Laurentian University, Sudbury.