Influência das variáveis operacionais e propriedades visuais de espuma no desempenho e controle da flotação de minério de ferro

Abstract

Reverse cationic quartz flotation is the most important step in iron ore concentration for pellet feed production, and its performance is crucial for optimal utilization of available reserves. In this context, this research proposes using a machine vision system to evaluate the behavior of froth properties during flotation and investigate their effects under different operating conditions. This study aims to take an integrated approach to process optimization, combining statistical analysis, computer vision, and technological evaluation of flotation cells, based on plant operating conditions, performance monitoring, and process control. Thus, opportunities were identified to maximize metallurgical recovery and adherence to the specified product quality. Nine industrial tests were conducted in the rougher stage using a Central Composite Design (CCD), investigating the effect of air flow rate and froth depth on process responses and froth properties, highlighting the importance of structured experimental approaches for optimization. Industrial tests were also conducted on conventional mechanical flotation, also in the rougher stage, to compare self-aerated and forced-air cell technologies, considering process variables and froth properties on the cell surface. The results demonstrated that forced-air cells provide better hydrodynamic conditions, resulting in better separation performance and lower operating costs. This technical finding supported an economic feasibility study for a plant subject to this study, aiming to modernize the entire conventional mechanical flotation cell fleet from self-aerated to forced-air. The result was attractive, generating an internal rate of return of 240.7%. Thus, this integration of operational conditions and machine vision proved effective in understanding and optimizing flotation performance.