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Discrete-Event Simulation of a Maintenance Policy with Multiple Scenarios

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Proceedings of the 28th International Symposium on Mine Planning and Equipment Selection - MPES 2019 (MPES 2019)

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Abstract

The current study offers a discrete-event simulation algorithm developed to reveal the effects of different maintenance work packages on the failure and the cost profiles of the mining systems. The algorithm is stochastic with two possible optimization criteria as maximizing system availability and minimizing maintenance cost for a given period. A numeric example is also provided to highlight how the effectiveness of a maintenance policy may differ with its content. In the example, 42 alternative maintenance policies were applied to an earthmover where corrective maintenance, preventive maintenance in regular inspections and opportunistic maintenance were located combinatorially for different inspection intervals. The total maintenance cost was dropped to $913,481 with an achievable production of 7,304 h for the optimal policy that included only corrective and opportunistic maintenance in the system-level, and excluded regular inspections.

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References

  1. Ben-Daya, M., Kumar, U., Murthy, D.P.: Introduction to Maintenance Engineering: Modelling, Optimization and Management, 1st edn. Wiley, Chichester (2016)

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  2. Sullivan, G.P., Pugh, R., Melendez, A.P., Hunt, W.D.: A Guide to Achieving Operational Efficiency. https://www.energy.gov/sites/prod/files/2013/10/f3/omguide_complete.pdf. Accessed 29 May 2019

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  4. Golbasi, O., Demirel, N.: A cost-effective simulation algorithm for inspection interval optimization: An application to mining equipment. Comput. Ind. Eng. 113, 525–540 (2017)

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Correspondence to Onur Golbasi .

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Turan, M.O., Golbasi, O. (2020). Discrete-Event Simulation of a Maintenance Policy with Multiple Scenarios. In: Topal, E. (eds) Proceedings of the 28th International Symposium on Mine Planning and Equipment Selection - MPES 2019. MPES 2019. Springer Series in Geomechanics and Geoengineering. Springer, Cham. https://doi.org/10.1007/978-3-030-33954-8_37

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  • DOI: https://doi.org/10.1007/978-3-030-33954-8_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33953-1

  • Online ISBN: 978-3-030-33954-8

  • eBook Packages: EngineeringEngineering (R0)

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