Optimization of the Copper Recovery from Printed Circuit Boards Using Artificial Intelligence as Strategy

Abstract

There is an increasing interest in the secondary sources of metals in order to compensate their potential supply deficit. Copper is the main component of printed circuit boards (PCBs) which is the main part of an electronic device. The manufacture of PCBs often releases huge amount of sludge, which contains copper. The process of copper leaching by hydrochloric acid solution was studied using experimental design methods using the Solver of Excel software. The parameters were simulated and simulated to evaluate the effect of the acid concentration and oxygen flow. The results obtained by prediction were compared with real experimental results. The intelligence modeling was confirmed by analysis of variance (ANOVA) and the model was able to predict the response. Through the investigation of response surface and contour curves, it was identified the conditions optimized for the process.