A mine-to-mill economic analysis model and spectral imaging-based tracking system for a copper mine

An economic analysis model is proposed for estimating the cost savings incurred in all operations, from blasting to milling, in a copper mine using spectral imaging-based tracking. A conventional mid-sized copper mine in Arizona with two ore types is used as a case study. First, a combined regression and discrete event simulation model of the material-handling network of the mine, constructed in Arena^TM, is used mainly to obtain throughput information at pits, crusher, and mills as well as the stochastic power consumption at each operation from mine to mill. The two ore types are assumed to be distinguished using a spectral imaging-based tracking method. The main components of the spectral imaging-based tracking method are a multispectral camera and a regression model consisting of partial least-squares, principal component, or logistic regression methods. Partial least-squares, principal component, and logistic regression method are then compared to select the best method to distinguish various ore types sampled from the mine. Finally, an economic analysis model based on tracking results fed to the simulation model is used to demonstrate the cost savings for each ore type as a function of the specific explosivegS energies. This is a preliminary study of the economic analysis of overall cost savings before testing in an actual copper mine.