Behavior Analysis of Transport Fleet in Open Pit Mine With Uncertain Data

Document Type : Original Article

Authors

1 َAssistant Professor, Mining, Technology and Engineering, Tarbiat Modares University, Tehran, Iran

2 Ph.D. Student, Department of Mining Engineering, Tarbiat Modares University

Abstract

In today's competitive world and trying to produce more and earn maximum profit in mining industry, analyzing the behavior of the fleet system is more important. Information available on the failure rate and repair time of system components is uncertain and imprecise so it is difficult reliability analyzing and prediction behavior of system based them. In the present research, behavior and reliability analysis of shovel System as an important equipment fleet of transport in open pit mine investigated under uncertainty using by fuzzy set theory and lambda-tau methodology. Cable shovel consists of seven subsystems (cable, bucket, stick, under carriage, engine and gearbox, pneumatic and electrical) in a series network configuration that have Weibull distribution for failure time.  Behavior of system is analyzed by using various reliability indices namely reliability, availability, MTBF (mean time between failures), failure rate and repair time. Results show that failure information has uncertainty less than repair times; and after 10 hours, RAM-index of system decrease. Behavior system analysis as helpful tool for select suitable maintenance strategy and improve performance system can be used.
 

Keywords

References

-­Adamyan, A., David, H., (2004), "System failure analysis through counters of Petri net models", Quality and Reliability Engineering International, Vol. 20, NO. 4, pp. 317–335.
 
-­Aksu, S., Aksu, S., Turan, O., (2006), "Reliability and availability of pod propulsion system", Journal of Quality and Reliability International, Vol. 22, No. 1, pp. 41–58.
 
-Cai, K.Y., (1996), "System failure engineering and fuzzy methodology an introductory overview", Fuzzy Sets system, Vol. 83, No. 2, pp. 113–133.
 
-Ebeling, C.E., (2001), "An Introduction to Reliability and Maintainability Engineering", New York: Tata McGrawHill Company Ltd.
 
-Elevli, S., Uzgoren, N., Elevli, B., (2008), "Correspondence analysis of repair data: A case study for electric cable shovels", Journal of Applied Statistics, Vol. 35 No. 8, pp. 901-908.
 
-Esmaeili, M., Bazzazi, A.A., Borna, S., (2011), "Reliability analysis of a fleet of loaders in sangan iron mine", Archives of Mining Sciences, Vol. 56, No. 4, pp. 629-640.
 
-Garg, H., Sharma, S. P., and Rani, M., (2012), "Behavior analysis of pulping unit in a paper mill with weibull fuzzy distribution function using ABCBLT technique", International Journal of Applied Mathematics and Mechanics, Vol. 8, No. 4, pp. 86–96.
 
-Garg,H. (2013), "Reliability analysis of repairable systems using Petri nets and vague Lambda-Tau methodology", ISA Transactions, Vol. 52, No. 1, pp. 6-18.
-Gupta, S., Ramkrishna, N., Bhattacharya, J. (2006), "Replacement and maintenance analysis of longwall shearer using fault tree technique", Transactions of the Institutions of Mining and Metallurgy, Section A: Mining Technology, Vol. 115 No. 2, pp. 49-58.
 
-Komal, S.h., Sharma, S.P., Kumar, D. (2010), "RAM analysis of repairable industrial system utilizing uncertain data", applied Soft Computing, Vol. 10, No. 4, pp. 1208-1221.
 
-Knezevic, J., Odoom, E.R., (2001), "Reliability modeling of repairable systems using Petri nets and Fuzzy Lambda-Tau methodology", Reliability Engineering and System Safety, Vol. 73, No. 1, pp. 1-17.
 
-Mon, D.L., Cheng, C.H., (1994), "Fuzzy system reliability analysis for components with different membership functions", Fuzzy Sets System, Vol. 64 No. 2, pp. 145–157.
 
-Panchal, D. and Kumar, D., (2015), "Stochastic behavior analysis of power generating unit in thermal power plant using fuzzy methodology", Opsearch, Vol. 53, No. 1, pp. 16–40.
 
-Rani, M., Sharma, S. P., and Garg, H., (2011), "Reliability analysis of press unit in paper plant using Weibull fuzzy distribution function", in Proceedings of the 16th Online World Conference on Soft computing in Industrial Application (WSC ’11).
 
-Samanta, B., Sarkar, B., Mukherjee, S.K., (2014), "Reliability modelling  and performance analyses of an LHD system in mining", Journal of The South African Institute of Mining and Metallurgy, Vol. 104, No. 1,
pp. 1-8.
 
-Sharma, R.K., Kumar, S., (2008), "Performance modeling in critical engineering systems using RAM analysis", Reliability Engineering and System Safety, Vol. 93 No. 6, pp. 913–919.
 
-Sharma, R.K., Kumar, D., Kumar, P., (2007), "FM—a pragmatic tool to model, analyze and predict complex behavior of industrial systems", Engineering Computations, Vol. 24 No. 4, pp. 319-346.
 
-Singer, D., (1990), "A fuzzy set approach to fault tree and reliability analysis", Fuzzy Sets System, Vol. 34, No. 2, pp. 145–155.
 
-Sharma, S.P., Garg, H., (2011), "Behavioral analysis of a urea decomposition system in a fertilizer plant", International Journal of Industrial and System Engineering, Vol. 8, No.3, pp. 271–97.
 
-Verma, M., Kumar, A., Singh, V., (2013), "Vague reliability assessment of combustion system using Petri nets and vague lambda‐tau methodology", Engineering Computations, Vol. 30, No. 5, pp. 665-681.
 
-Verma, M., Kumar, A., (2014), "A novel general approach to evaluating the reliability of gas turbine system", Engineering Applications of Artificial Intelligence, Vol. 28, pp. 13-21.
 
-Vishwakarma, Y. and Sharma, S.P., (2015), "Uncertainty analysis of an industrial system using Intuitionistic Fuzzy Set Theory", International Journal of System Assurance Engineering and Management. Vol. 7, No. 1,
pp. 73–83.
 
-Zadeh, L.A., (1965), "Fuzzy sets", Information and Control. Vol. 8, No. 3, pp. 338-353.

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