Resumo:
Glycerol is the main by-product of the biodiesel industry and new technological routes have been tried for its use due to the increase in the world production of the biofuel. One of the possible applications is in the production of acrylonitrile, a product with applications in synthetic fibers and resins. The main route for obtaining acrylonitrile is through the ammoxidation of propylene. The high cost of propylene encouraged studies to obtain acrylonitrile via glycerol ammoxidation, which is a sustainable raw material of low commercial value. In this context, this work developed a new process for the production of acrylonitrile (with commercial purity of 99.5% w/w) from glycerol, passing through the purification of this glycerol to remove impurities, followed by the glycerol ammoxidation reaction and finally the purification of the acrylonitrile produced. Due to its high commercial value, the main by-product of the process, acetonitrile, was purified to HPLC grade (99.9% w/w purity). The process optimization was carried out using artificial neural networks and genetic algorithm aiming at the best design/operation conditions for greater economy. The risk analysis using Monte Carlo simulation tolerated that the new process is viable in the tested scenarios (which consider simultaneous variations in the prices of raw materials, products and inputs), experimenting with the psychological criteria (NPV/Total Investment >=2 and IRR >= 21,5%) in 73% of the scenarios tested. Finally, an economic comparison with the conventional process (via propylene) was carried out and it was found that the new process has the potential to be more viable, in economics terms, than the conventional process.