A methodology to predict the stability status of mine rock slopes is proposed. Two techniques of multivariate statistics are used: principal component analysis and discriminant analysis. Firstly, principal component analysis was applied in order to change the original qualitative variables into quantitative ones, as well as to reduce data dimensionality. Then, a boosting procedure was used to optimize the resulting function by the application of discriminant analysis in the principal components. In this research two analyses were performed. In the first analysis two conditions of slope stability were considered: stable and unstable. In the second analysis three conditions of slope stability were considered: stable, overall failure and failure in set of benches. A comprehensive geotechnical database consisting of 18 variables measured in 84 pit-walls all over the world was used to validate the methodology. The discriminant function was validated by two different procedures, internal and external validations.
In order to elaborate a mine plan, it is necessary to adopt hourly production parameters for the equipment available for its execution. This ResumoPara elaboração de planos de lavra, é necessário adotar parâmetros de produtividade horária dos equipamentos disponíveis para sua execução. Esses equipamentos devem estar em sincronia com a capacidade produtiva das operações unitárias de lavra mineira: perfuração de rocha, desmonte, carregamento e transporte. Esse estudo trata da estimativa de índices de produtividade horária das operações de carregamento e transporte com a utilização de regressões múltiplas. Através da utilização da base de dados do sistema de gerenciamento operacional de uma mina, foram geradas equações que explicam o ciclo produtivo de cada um dos equipamentos de carga e das frotatransporte. Conhecendo-se o comportamento das principais variáveis que exercem influência na produtividade horária, foi possível estimar esse índice e garantir alta exequibilidade para o plano de lavra, pois os índices obtidos foram muito próximos dos reais. A formulação do modelo foi realizada de forma simples, utilizando-se de conceitos estatísticos e de ferramentas computacionais, sendo o modelo sustentado por uma boa correlação entre as variáveis. Esse fator foi decisivo para que esse estudo obtivesse bons resultados na execução dos planos de lavra estudados.Palavras chave: Plano de lavra, produtividade horária, regressões múltiplas, gerenciamento operacional.
Edilaila Fernandes Moraes et al. ResumoEsse trabalho tem seu enfoque no problema de blendagem de produtos de minério de ferro, estocados nos pátios da mina Cauê, da Companhia Vale do Rio Doce, em Itabira, Minas Gerais, para a composição de lotes. Propõe-se um modelo de programação linear por metas que visa a determinar os locais de retomada dos produtos estocados, de tal forma que a mistura atenda aos limites de especificações de qualidade e quantidade preestabelecidos pelo cliente e satisfaça as restrições operacionais dos pátios. O modelo de programação matemática desenvolvido foi implementado no modelador e otimizador LINGO 9.0, interfaceando com planilhas do EXCEL 2000, possibilitando a utilização e exportação de dados em um ambiente familiar à empresa de mineração. O sistema desenvolvido foi validado comparando-se os resultados obtidos com os produzidos manualmente pela empresa. Os resultados computacionais apresentados comprovaram que é possível prover uma melhora na composição dos lotes através do modelo proposto. Palavras-chave:
In all mining projects, transportation costs influence net profit, justifying economic feasibility studies before transport fleet acquisition or replacement. These studies can provide the best loading and hauling equipment combination to meet production demands at lower costs by evaluating the alternatives available in the market. When there is more than one solution with similar costs and technical specifications, decision-making technics were considered to be used. Herein is presented the case of selecting hauling trucks used to transport run of mine (ROM) ore at a bauxite mining company, located in the State of Minas Gerais, Brazil, using the Multi-Criteria Decision Aid methodology (MCDA).
Historically, since the 60's, traditional mine planning consists of several distinct stages: 1) Definition of the ultimate pit-the portion of the blocks that results in the greatest total value; 2) Pushback selection-based on the generation of nested pits, obtained with the change in the value of the ore price; 3) Long-term production scheduling. Although considered quite satisfactory, this methodology presents some flaws: The stages, even if considered individually optimal, may not be when put together. The opportunity cost is not considered and the cutoff is fixed. Due to the recent computational advances, a new technique has been growing and is more reliable: the direct block sequencing. In this methodology, the steps are consolidated into only one process, improving the economic results, reducing the total execution time and obtaining, in fact, an optimal planning. The aim of this work is to compare the results of the two planning methods applied in a database of a Brazilian iron ore mine and to show the real advantages and disadvantages of each one. To solve the direct block sequencing technique, Doppler was used, a tool developed by Delphos Mine Planning Laboratory, located at the University of Chile. The traditional methodology was executed through Whittle software. Lastly, a medium-term scheduling was performed using Deswik software.
Hydraulic fracturing emerges currently, all over the world, as one of the more strategic techniques used by companies in the oil exploitation sector. This technique is characterized by its high productivity and profit in relation to conventional methods of hydrocarbon exploitation. However, in many countries, as is the case of Brazil, there are several divergences considering the employment of this methodology. Many renowned researchers attest that there are several irreversible environmental impacts generated by the use of this methodology. Among the main environmental impacts are the risk of groundwater level contamination, the risk of surface subsidence, and the risk of the environment contamination with fluids used in the process of the oil and gas extraction.
SUMMARYIndicator kriging has been applied to the study of failure mechanisms in a mine slope in Minas Gerais, Brazil, to estimate potential failure risks in limited areas along this slope. Timbopeba Mine, Vale Company, is an open pit iron mine situated in the Quadrilátero Ferrífero, a very important mining district in Minas Gerais. A slope excavated in quartzite with a maximum height of 200 m at the time of this study, has presented many failure problems involving the sliding of blocks formed by discontinuities. These blocks are of limited size in comparison to the dimensions of the overall slope. They appear along the entire slope, wherever discontinuity orientations have led to the kinematic feasibility of these blocks. Geostatistics permits the estimation of local failure probability distributions associated to these local failures, which would not be possible with traditional statistical models. The geostatistical method employed in this study, indicator kriging, is quite suitable because it is unnecessary to assume a particular global distribution of the phenomena being modeled. The model was used for locating areas with a great tendency for sliding failure, as it considers the local spatial variability of discontinuity orientations.
The construction of block models with an estimation of grades in situ is a common practice throughout resource evaluation. However, this information is not enough to understand the behavior of the ore in the beneficiation process. Geometallurgy proposes the addition of the ore´s metallurgical behavior in the block model, making it more dependable and adhering when it comes to production capacity, which generates financial earnings and brings risks down. Mass recovery is an important metallurgical variable for economic and mine planning. This is often underused, due to the lack of data, making it hard to use in the planning process. In order to achieve better use of the data available, the multiple regression analysis technique was used so as to develop a statistic model that would relate the mass recovery with the in situ grades, allowing that deposit regions with no available metallurgical information have an estimation of this variable's values.
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