Comparison of capex models for mining
DOI:
https://doi.org/10.33448/rsd-v9i12.11013Keywords:
CAPEX; Mine operation; Cost estimation.Abstract
In order to estimate the costs of mining enterprises correctly before the construction of the mining it is important to determine the viability of the mineral deposit. There is no standardization of the methods of estimating operating costs of these projects. Regression-based equations are used to forecast costs and, as a result, differences arise between the results. This study analyses different estimation models with a focus on capital costs, that is, those associated with the necessary infrastructure for opening an open pit mine - mining and processing. Two methodologies were evaluated in order to determine which is more assertive. Monte Carlo simulations were performed to check the compatibility between the methods based on the limits of the analysed models. The study was able to determine which model underestimates costs, with the risk of pointing out the economic viability of projects that are not viable in light of the real cost.
References
Adrien Rimélé, M., Roussos Dimitrakopoulos., and Michel Gamache. (2018). “A Stochastic Optimization Method with In-Pit Waste and Tailings Disposal for Open Pit Life-of-Mine Production Planning.” Resources Policy 57(February): 112–21. http://dx.doi.org/10.1016/j.resourpol.2018.02.006.
Bagherpour, R. 2007. “Technical and Economical Optimization of Surface Mining Processes – Development of a Data Base and a Program Structure for the Computer-Based Selection and Dimensioning of Equipment in Surface Mining Operations.” Wirtschaftswissenschaften der Technischen Universität Clausthal.
Carriconde, M. C. 2010. “Verificação Da Aplicabilidade Do Programa Mafmo Com Ferramenta Auxiliar Na Estimativa de Custos Em Projetos Conceituais.” : 136.
Clement, G. K. R., Miller, & Patrick H., Geehan. (1979). Capital And Operating Cost Estimating System Handbook, Mining, Retorting And Upgrading Of Oil Shale In Colorado, Utah And Wyoming. California.
Clements, Kenneth W., & Jiawei, S. (2017). “Simplifying The Big Mac Index.” Journal of International Financial Management & Accounting 28(1): 86–99. http://doi.wiley.com/10.1111/jifm.12058.
D’Arrigo, R. F. (2012). “Modelo de Estimativa de Custos Operacionais e de Capital Em Projetos de Mineração Em Fase Conceitual Baseado No Modelo de O’Hara.” Recuperado de: http://search.ebscohost.com/login.aspx?direct=true&db=edsndl&AN=edsndl.oai.union.ndltd.org.IBICT.oai.agregador.ibict.br.BDTD.oai.bdtd.ibict.br.UFRGS.oai.www.lume.ufrgs.br.10183.96382&lang=pt-br&site=eds-live.
Earl, D. J., & Michael W. D. (2008). “Monte Carlo Simulations.” In, 25–36. http://link.springer.com/10.1007/978-1-59745-177-2_2.
Franco-Sepulveda, G., Carlos C., & Pineda, C. (2017). “NPV Risk Simulation of an Open Pit Gold Mine Project under the O’Hara Cost Model by Using GAs.” International Journal of Mining Science and Technology 27(3): 557–65. http://dx.doi.org/10.1016/j.ijmst.2017.03.004.
Júnior, I. S. M. 2011. “Diretrizes Fundamentais Para Um Estudo de Avaliação Econômica de Empreendimentos de Mineração: Um Estudo Bibliográfico.” Universidade Federal de Ouro Preto.
Käki, M., & Aula, P. (2005). “Findex: Improving Search Result Use through Automatic Filtering Categories.” Interacting with Computers 17(2): 187–206. https://academic.oup.com/iwc/article-lookup/doi/10.1016/j.intcom.2005.01.001.
Nourali, H., & Morteza, O. 2019. “Mining Capital Cost Estimation Using Support Vector Regression (SVR).” Resources Policy 62: 527–40.
Pereira, A. S.., et al (2018). Metodologia da Pesquisa Científica Método Qualitativo, Quantitativo Ou Quali-Quanti. https://repositorio.ufsm.br/bitstream/handle/1/15824/Lic_ Comput acao_Metodologia-Pesquisa-Cientifica.pdf?sequence=1.
Runge, I. C. (1998). Mining Economics and Strategy. SME.
Thompson, R. J. (2013). “Principles of Mine Haul Road Design and Construction.”
Thompson, R. J., & Visser, A. T. (2003). “Mine Haul Road Fugitive Dust Emission and Exposure Characterisation.” Sustainable World 8(January): 103–12.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2020 Guilherme Garcia Oliveira Queiroz; Felipe Ribeiro Souza; Bárbara Isabela da Silva Campos
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
1) Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2) Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3) Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
