Citas bibligráficas
Quesada, C., (2015). Identificación de factores operacionales y su influencia en la producción de una flota de volquetes Volvo FMX 6x4 en la empresa NCA servicios de la minera Argentum [Tesis, Universidad Nacional de Ingeniería]. http://hdl.handle.net/20.500.14076/3948
Quesada, C., Identificación de factores operacionales y su influencia en la producción de una flota de volquetes Volvo FMX 6x4 en la empresa NCA servicios de la minera Argentum [Tesis]. : Universidad Nacional de Ingeniería; 2015. http://hdl.handle.net/20.500.14076/3948
@misc{renati/706915,
title = "Identificación de factores operacionales y su influencia en la producción de una flota de volquetes Volvo FMX 6x4 en la empresa NCA servicios de la minera Argentum",
author = "Quesada De la Cruz, Carlos Gustavo",
publisher = "Universidad Nacional de Ingeniería",
year = "2015"
}
This work of investigation aims to the identification of the main operational factors and determine their influence on the production of a fleet of equipment hauling ore and waste. The identification process will be held using statistical tools and direct observation while to quantify the influence of factors in the operation be developed mathematical models. The process of mathematical modeling of operational factors is performed by executing a series of stages statistics ordered, as this will ensure the quality and accuracy of mathematical production function and could generate reliable predictions for optimal productivity analysis in hauling activity. The research study was divided into two main parts, the first part of the description of the system makes hauling the mining operation, identifying factors via data and detailed observation in the field. After the first part of the statement it was performed the problem and their general and specific objectives to find possible solutions. The second part of this study using statistical methods needed to create function statistics, such as randomness test, evaluation of outliers, stationary analysis, determination of correlation coefficient analysis and Pearson coefficient of determination and finally an analysis multivariate regression where the mathematical function determine production. This analysis finally allows a mathematical model of production in order to obtain proposals for reliable and highly productive improvement.
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