Production Capacity Insurance Considering Reliability, Availability, and Maintainability Analysis
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 8, Issue 2
Abstract
Production scheduling is one of the most substantial indicators in achieving short-term, medium-term, and long-term production planning goals. Satisfying this indicator can remarkably reduce total costs and enhance profitability. The haulage system significantly affects the mine production scheduling. Indeed, the uncertain nature of the haulage system causes considerable differences between the nominal and actual haulage production capacity. Thus, it is necessary to predict the haulage fleet size considering various variables to maintain production scheduling and reach nominal production capacity. Although the haulage fleet size plays a crucial role in satisfying medium-term production planning goals, it is often determined under steady-state conditions without quantifying and analyzing uncertain variables such as reliability, availability, and maintainability (RAM). In this study, a simulation optimization algorithm is developed to determine the most optimal fleet requirements considering influential factors such as RAM analysis, production scheduling, material flow rate, and stochastic environmental and operational phenomena. The proposed methodology addresses the haulage fleet size at one stage by developing a parallel combination of mixed-integer programming and discrete-event simulation. This approach has been validated using a haulage fleet operation at the Sungun mine. In this case, the analysis procedure is accomplished by determining the optimal haulage fleet size with and without considering RAM during the mining operation. Then, all mining zones are assessed based on the number of failures and loss of production capacity. During 1,500 operation hours, the lost production capacity in Mining Zones 1, 2, and 3 were 346,000, 319,000, and 481,900 t, respectively. Also, a sensitivity analysis is conducted to identify the impact of the failure and downtime of each subsystem of the haul trucks on the haulage production capacity. Thus, the engine subsystem was the most critical truck’s subsystem. The findings showed the desired performance of the proposed methodology.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or codes that support the findings of this study are available from the corresponding author upon reasonable request. It includes Simulation Model and Optimization Codes.
Acknowledgments
The authors appreciate the operation and maintenance department at the Sungun copper mine. Also, the authors would thank Mr. Araz Sokhandan for his assistance during project implementation.
References
Abolghasemian, M., A. Ghane Kanafi, and M. Daneshmandmehr. 2020. “A two-phase simulation-based optimization of hauling system in open-pit mine.” Iran. J. Manage. Stud. 13 (4): 705–732. https://doi.org/10.22059/ijms.2020.294809.673898.
Abolhasani, Z. H., R. M. Marian, and L. Loung. 2013. “Optimization of multi-commodities consumer supply chains for-part I-modeling.” J. Comput. Sci. 9 (12): 1830. https://doi.org/10.3844/jcssp.2013.1830.1846.
Afrapoli, A. M., M. Tabesh, and H. Askari-Nasab. 2019. “A transportation problem-based stochastic integer programming model to dispatch surface mining trucks under uncertainty.” In Proc., 27th Int. Symp. on Mine Planning and Equipment Selection-MPES 2018. Berlin: Springer.
Alkass, S., K. El-Moslmani, and M. AlHussein. 2003. “A computer model for selecting equipment for earthmoving operations using queuing theory.” In Proc., CIB W78’s 20th Int. Conf. on Construction IT, Construction IT Bridging the Distance, 1–8. Enschede, Netherlands: ITC Digital Library.
Altiok, T., and B. Melamed. 2010. Simulation modeling and analysis with Arena. Cambridge, MA: Academic Press.
Burt, C., L. Caccetta, and P. Welgama. 2005. “Models for mining equipment selection.” In Proc., Int. Congress on Modelling and Simulation, 170–176. Canberra, Australia: Modelling and Simulation Society of Australia and New Zealand.
Cox, D. 1972. “The statistical analysis of dependencies in point processes.” In Stochastic point processes, 55–66. New York: Wiley.
Deep, K., K. P. Singh, M. L. Kansal, and C. Mohan. 2009. “A real coded genetic algorithm for solving integer and mixed integer optimization problems.” Appl. Math. Comput. 212 (2): 505–518. https://doi.org/10.1016/j.amc.2009.02.044.
Fadin, A. Y. F., and A. O. Moeis. 2017. “Simulation-optimization truck dispatch problem using look-ahead algorithm in open pit mines.” Int. J. GEOMATE 13 (36): 80–86. https://doi.org/10.21660/2017.36.2843.
Faraji, R. 2013. A comparison between linear programming and simulation models for a dispacthing system in open pit mines. Montreal: École Polytechnique de Montréal.
Fioroni, M. M., L. A. G. Franzese, T. J. Bianchi, L. Ezawa, and L. R. Pinto. 2008. “Concurrent simulation and optimization models for mining planning.” In Proc., 40th Conf. on Winter Simulation, 759–767. New York: IEEE. https://doi.org/10.1109/WSC.2008.4736138.
Hall, R. A., and L. K. Daneshmend. 2003. “Reliability modelling of surface mining equipment: Data gathering and analysis methodologies.” Int. J. Surf. Min. Reclam. Environ. 17 (3): 139–155. https://doi.org/10.1076/ijsm.17.3.139.14773.
Isnafitri, M., C. Rosyidi, and A. Aisyati. 2021. “A truck allocation optimization model in open pit mining to minimize investment and transportation costs.” In Proc., IOP Conf. Series: Materials Science and Engineering. Bristol, UK: IOP Publishing.
Krause, A., and C. Musingwini. 2007. “Modelling open pit shovel-truck systems using the machine repair model.” J. S. Afr. Inst. Min. Metall. 107 (8): 469–476.
Lu, C., C.-W. Fei, Y.-W. Feng, Y.-J. Zhao, X.-W. Dong, and Y.-S. Choy. 2021. “Probabilistic analyses of structural dynamic response with modified Kriging-based moving extremum framework.” Eng. Fail. Anal. 125 (Jul): 105398. https://doi.org/10.1016/j.engfailanal.2021.105398.
Lu, C., C.-W. Fei, H.-T. Liu, H. Li, and L.-Q. An. 2020. “Moving extremum surrogate modeling strategy for dynamic reliability estimation of turbine blisk with multi-physics fields.” Aerosp. Sci. Technol. 106 (Nov): 106112. https://doi.org/10.1016/j.ast.2020.106112.
MathWorks Inc. 2015. MATLAB software package, simevents toolbox help. Portola Valley, CA: MathWorks Inc.
Modarres, M. 2006. Risk analysis in engineering: Techniques, tools, and trends. London: CRC Press.
Moniri-Morad, A., M. Pourgol-Mohammad, H. Aghababaei, and J. Sattarvand. 2018. “Reliability-based regression model for complex systems considering environmental uncertainties.” In Proc., Probabilistic Safety Assessment and Management (PSAM 14). Los Angeles: International Association for Probabilistic Safety Assessment and Management.
Moniri-Morad, A., M. Pourgol-Mohammad, H. Aghababaei, and J. Sattarvand. 2019a. “A methodology for truck allocation problems considering dynamic circumstances in open pit mines, case study of the Sungun copper mine.” Rudarsko-geološko-naftni zbornik 34 (4): 18. https://doi.org/10.17794/rgn.2019.4.6.
Moniri-Morad, A., M. Pourgol-Mohammad, H. Aghababaei, and J. Sattarvand. 2019b. “Capacity-based performance measurements for loading equipment in open pit mines.” J. Central South Univ. 26 (6): 1672–1686. https://doi.org/10.1007/s11771-019-4124-5.
Moniri-Morad, A., M. Pourgol-Mohammad, H. Aghababaei, and J. Sattarvand. 2019c. “Reliability-based covariate analysis for complex systems in heterogeneous environment: Case study of mining equipment.” Proc. Inst. Mech. Eng., Part O: J. Risk Reliab. 233 (4): 593–604. https://doi.org/10.1177/1748006X18807091.
Morad, A. M., M. Pourgol-Mohammad, and J. Sattarvand. 2013. “Reliability-centered maintenance for off-highway truck: Case study of sungun copper mine operation equipment.” In Proc., ASME Int. Mechanical Engineering Congress & Exposition. New York: ASME. https://doi.org/10.1115/IMECE2013-66355.
Morad, A. M., M. Pourgol-Mohammad, and J. Sattarvand. 2014. “Application of reliability-centered maintenance for productivity improvement of open pit mining equipment: Case study of Sungun copper mine.” J. Central South Univ. 21 (6): 2372–2382. https://doi.org/10.1007/s11771-014-2190-2.
Moradi-Afrapoli, A., S. Upadhyay, and H. Askari-Nasab. 2021. “Truck dispatching in surface mines-Application of fuzzy linear programming.” J. S. Afr. Inst. Min. Metall. 121 (9): 1–8. https://doi.org/10.17159/2411-9717/522/2021.
Salimi, S., M. Mawlana, and A. Hammad. 2018. “Performance analysis of simulation-based optimization of construction projects using high performance computing.” Autom. Constr. 87 (Sep): 158–172. https://doi.org/10.1016/j.autcon.2017.12.003.
Souza, M. J., I. M. Coelho, S. Ribas, H. G. Santos, and L. H. D. C. Merschmann. 2010. “A hybrid heuristic algorithm for the open-pit-mining operational planning problem.” Eur. J. Oper. Res. 207 (2): 1041–1051. https://doi.org/10.1016/j.ejor.2010.05.031.
Torkamani, E., and H. Askari-Nasab. 2015. “A linkage of truck-and-shovel operations to short-term mine plans using discrete-event simulation.” Int. J. Min. Miner. Eng. 6 (2): 97–118. https://doi.org/10.1504/IJMME.2015.070367.
Vagenas, N., N. Runciman, and S. R. Clément. 1997. “A methodology for maintenance analysis of mining equipment.” Int. J. Surf. Min. Reclam. Environ. 11 (1): 33–40. https://doi.org/10.1080/09208119708944053.
Zhang, Y., S. Li, and Q. Cai. 1990. “Optimization criteria for computer controlled truck dispatching system.” In Proc., 22nd APCOM Conf., 295–306. Berlin: Library of Technische Univ.
Information & Authors
Information
Published In
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Nov 10, 2021
Accepted: Jan 28, 2022
Published online: Mar 28, 2022
Published in print: Jun 1, 2022
Discussion open until: Aug 28, 2022
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.
Cited by
- Amin Moniri-Morad, Javad Sattarvand, A comparative study between the system reliability evaluation methods: case study of mining dump trucks, Journal of Engineering and Applied Science, 10.1186/s44147-023-00272-y, 70, 1, (2023).
- Milad Abolghasemian, Armin Ghane Kanafi, Maryam Daneshmand-Mehr, Simulation-Based Multiobjective Optimization of Open-Pit Mine Haulage System: A Modified-NBI Method and Meta Modeling Approach, Complexity, 10.1155/2022/3540736, 2022, (1-15), (2022).