Reconciliation of sampling data and heterogeneity analysis of a bauxite mine in Poços de Caldas/MG, in Brazil

Abstract

Abstract Reconciliation plays a key role in controlling and analysing mine operations. It consists in comparing model estimates with actual results produced by the plant, being used as an indicator, a monitoring tool. Discrepancies between these values are common in the mining industry and they highlight problems during processing steps. However, these discrepancies do not necessarily need to be brought to zero, as long as their order of magnitude is understood. Prognostication, a new concept that seeks to replace reactive reconciliation, aims to raise and correct the real causes of these variations. A common cause of this type of problem is sampling, which in most cases is not performed correctly, providing biased samples and compromising reconciliation analyses. The present study reports, evaluates and improves reconciliation in a bauxite mine located in the city of Poços de Caldas/MG, in Brazil and reports on a study of the heterogeneity of the ore. A common practice of the bauxite mines in Poços de Caldas is to carry out the last stage of sampling manually from the trucks before the ore goes to the treatment plant. The data evidenced that this sampling is biased and systematically overestimates the planned ore grades. In addition, it has been confirmed that the best alternative for the company is to implement a conveyor belt sampler collecting increments every 15 minutes. This method shows the best adherence to the plan, that is 100.7% for available alumina and 83% for reactive silica.

Keywords

• reconciliation
• sampling
• Theory of Sampling
• TOS
• sampling errors
• automatic sampler
• prognostication