Support vector machine regression analysis of LHD failures

References

• K. Xu, M. Xie, L.C. Tang, and S.L. Ho, Application of neural networks in forecasting engine systems reliability, Appl. Soft Comput. J. 2 (2003), pp. 255–268.10.1016/S1568-4946(02)00059-5
   Google Scholar
• B. Scholkoff and A.J. Smola, Learning with kernels – support vector machines, regularization, optimization, and beyond, The MIT Press, Cambridge, MA, 2002.
   Google Scholar
• M.D.C. Moura, E. Zio, I.D. Lins, and E. Droguett, Failure and reliability prediction by support vector machines regression of time series data, Reliability Engineering and System Safety 96(11) (2011), pp. 1527–1534.10.1016/j.ress.2011.06.006
   Web of Science ®Google Scholar
• S. Elevli and B. Elevli, Performance measurement of mining equipments by utilizing OEE, Acta Montanistica Slovaca 15 (2010), pp. 95–101.
   Web of Science ®Google Scholar
• S.K. Roy, M.M. Bhattacharyya, and V.N.A. Naikan, Maintainability and reliability analysis of a fleet of shovels, Inst. Min. Metall. Trans. Sect. A: Min. Technol. 110 (2001), pp. A163–A171.
   Web of Science ®Google Scholar
• B. Samanta, B. Sarkar, and S.K. Mukherjee, Reliability assessment of hydraulic shovel system using fault trees, Inst. Min. Metall. Trans. Sect. A: Min. Technol. 111 (2002), pp. A129–1135.
   Web of Science ®Google Scholar
• Y.-H. Liang, Analyzing and forecasting the reliability for repairable systems using the time series decomposition method, Int. J. Qual. Reliab. Manage. 28 (2011), pp. 317–327.10.1108/02656711111109919
   Google Scholar
• N. Vagenas, N. Runciman, and S. Clément, A methodology for maintenance analysis of mining equipment, Int. J. Surf. Min. Reclam. Environ. 11 (1997), pp. 33–40.10.1080/09208119708944053
   Google Scholar
• G. Yuriy and N. Vayenas, Discrete-event simulation of mine equipment systems combined with a reliability assessment model based on genetic algorithms, Int. J. Surf. Min. Reclam. Environ. 22 (2008), pp. 70–83.10.1080/17480930701589674
   Google Scholar
• B. Samanta, B. Sarkar, and S.K. Mukherjee, Reliability analysis of shovel machines used in an open cast coal mine, Miner. Resour. Eng. 10 (2001), pp. 219–231.10.1142/S0950609801000610
   Google Scholar
• S. Elevli, N. Uzgören, and B. Elevli, Correspondence analysis of repair data: a case study for electric cable shovels, J. Appl. Stat. 35 (2008), pp. 901–908.10.1080/02664760802125627
   Web of Science ®Google Scholar
• R.A. Hall, P.F. Knights, and L.K. Daneshmend, Pareto analysis and condition-based maintenance of underground mining equipment, Inst. Min. Metall. Trans. Sect. A: Min. Technol. 2000 (2000), pp. A14–A22.
   Google Scholar
• A. Gustafson, H. Schunnesson, and U. Kumar, Reliability analysis and comparison between automatic and manual load haul dump machines, Qual. Reliab. Eng. Int. (2013), Article in Press. November 28, 2013, DOI: 10.1002/qre.1610
   Web of Science ®Google Scholar
• C.-C. Chang and C.-J. Lin, LIBSVM: A Library for support vector machines, ACM Trans. Intell. Syst. Technol. 2 (2011), art. No. 27. pp. 1–27.
   Web of Science ®Google Scholar
• M. Hofmann and R. Klinkenberg, RapidMiner: Data Mining Use Cases and Business Analytics Applications (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series), Boca Raton, FL: CRC Press, October 25, 2013.
   Google Scholar
• C.J.C. Burges, A tutorial on support vector machines for pattern recognition, Data Min. Knowl. Discov. 2 (1998), pp. 121–167.10.1023/A:1009715923555
   Web of Science ®Google Scholar
• K.-R. Muller, S. Mika, G. Ratsch, K. Tsuda, and B. Scholkopf, An introduction to kernel-based learning algorithms, IEEE Trans. Neural Networks 12 (2001), pp. 181–201.10.1109/72.914517
   PubMed Web of Science ®Google Scholar
• O. Chapelle, V. Vapnik, O. Bousquet, and S. Mukherjee, Choosing multiple parameters for support vector machines, Mach. Learn. 46 (2002), pp. 131–159.10.1023/A:1012450327387
   Web of Science ®Google Scholar
• C.-W. Hsu and C.-J. Lin, A comparison of methods for multiclass support vector machines, IEEE Trans. Neural Networks 13 (2002), pp. 415–425.
   PubMed Web of Science ®Google Scholar
• A.J. Smola and B. Schölkopf, A tutorial on support vector regression, Stat. Comput. 14 (2004), pp. 199–222.10.1023/B:STCO.0000035301.49549.88
   Web of Science ®Google Scholar
• S. Chatterjee, A. Dash, and S. Bandopadhyay, Ensemble support vector machine algorithm for. reliability estimation of a mining machine, Qual. Reliab. Eng. Int. (2014), Article in Press. June 26, 2014, DOI: 10.1002/qre.1686
   Google Scholar