Regression model applied to a two-stage charger rock in a surface mining operation

Abstract

The productivity of a rock charger operates on a front surface mining is influenced by many variables. We identified those considered most important and for a type charger model number measurements were taken in the field. Using linear regression expressions that allow predicting the dependent variable as a function of the independent variables were deducted. The dependent variables were identified : production tonnage , fill factor , and delay characteristics of the excavation. The independent variables were : bench height , boot size and fragmentation. Least squares system is used to predict the performance and cost given certain values ​​of the remaining variables in the regression equation but there is the problem of selecting the dependent variable. Two or more variables in the system might seem equally dependent , since the process to test significance of the variable can be iffy .