Uso de modelos paramétricos para estimativas de investimento aplicadas às etapas de britagem primária e secundária de minério de ferro

Abstract

Reliable cost and investment estimates raise the reliability of the economic and financial evaluation of projects. This evaluation aims to validate the continuation of studies and projects of mining sector. Primary and secondary crushing stages in mining can be considered as the initial stages of mineral processing, usually after the stages of blasting, loading and hauling. In order to determine the parametric estimator models, this study proposes multivariate regression models using the methodology suggested by Sayadi, Khalesi, Borji (2013). These models were developed using a multivariate regression (MVR) technique based on principal component analysis (PCA). The results of the evaluation of the models showed that the mean relative error rates were 17.7% using two main components and reached 9.7% when the original main components were maintained (lower than the multivariate regression using the stepwise method with error of 10.9%). In complementary analysis were adjusted the equations proposed by O'Hara in 1978 and 1988, seeking to evaluate if these equations can reflect the reality of mining costs and investments in Brazil in 2019. The average errors found using the adjustment factors proposed with the optimization tool were 17% for the updated equations of 1988 and 20% for the original equations of 1978, thus showing that these models still have good applicability for feasibility studies.