Análise de dados de sistemas de despacho

Abstract

The use of electronic monitoring in equipment, in the transport of material used in mining, makes it possible to obtain various information about the process, acting as an aid tool in decision making. The characteristics of mining end up making it expensive and complex, so that this type of solution acts as an ally of the sector. Given this situation, it is proposed to develop research that can contribute to the identification of indicators and indicators, allowing a better understanding of the variables involved. The methodology used is that of the case study, using different variables, produced by a transport vehicle, used in the mining process and basic by the use of an electronic dispatch system. For this, it was implemented using the different approaches of data analysis, among them the use of clusters in k-means and machine learning in KNN (Algorithm of the closest neighbors), as which allows to obtain an understanding of the best process. It was also possible to perceive the correlations between the variables used as well as the possibility of realizing fuel consumption, the variable very much within the washing process, through common data in dispatch systems.