ISSN 2594-357X
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Abstract
The process of particle size reduction by grinding is inherently inefficient and involves high capital and operating costs. In particular, ball milling is one of the important unit operations in the iron ore pelletizing process. The mill product, due to its physical properties, determines the efficiency of subsequent stages of classification, filtration and pelletizing, thus impacting the quality of iron ore pellets. The work demonstrates the application of the population balance model in the optimization of a full-scale ball mil circuit grinding pellet fines with the aim to evaluate the optimal solids concentration to improve iron ore pellet quality. Initially, detailed experimentation was carried out in a 25.4 cm diameter batch mill and a relationship for mill scale-up using a linear population balance model in wet grinding systems was established. The selection and breakage parameters and the specific selection functions were determined for pellet feed iron ore. It was possible to identify the non-normalizable nature of the breakage functions of the ore studied, which were modeled properly. Afterwards, as a result of incorporating the specific selection functions and breakage functions into the linear population balance model, it was possible to predict product size distributions in the pilot and plant scale mills (0.416 and 5.18 m diameter, respectively) from data obtained in the 25.4 cm diameter mill. Finally, with this scale-up procedure it was possible to appraise the plant scale optimization via laboratory scale grinding mill tests. The effects of changing percent solids were assessed in order to improve the industrial mill performance and the optimal value should be in the range from 76 to 80%.
The process of particle size reduction by grinding is inherently inefficient and involves high capital and operating costs. In particular, ball milling is one of the important unit operations in the iron ore pelletizing process. The mill product, due to its physical properties, determines the efficiency of subsequent stages of classification, filtration and pelletizing, thus impacting the quality of iron ore pellets. The work demonstrates the application of the population balance model in the optimization of a full-scale ball mil circuit grinding pellet fines with the aim to evaluate the optimal solids concentration to improve iron ore pellet quality. Initially, detailed experimentation was carried out in a 25.4 cm diameter batch mill and a relationship for mill scale-up using a linear population balance model in wet grinding systems was established. The selection and breakage parameters and the specific selection functions were determined for pellet feed iron ore. It was possible to identify the non-normalizable nature of the breakage functions of the ore studied, which were modeled properly. Afterwards, as a result of incorporating the specific selection functions and breakage functions into the linear population balance model, it was possible to predict product size distributions in the pilot and plant scale mills (0.416 and 5.18 m diameter, respectively) from data obtained in the 25.4 cm diameter mill. Finally, with this scale-up procedure it was possible to appraise the plant scale optimization via laboratory scale grinding mill tests. The effects of changing percent solids were assessed in order to improve the industrial mill performance and the optimal value should be in the range from 76 to 80%.
Keywords
Population balance model; Optimization; Breakage and Selection functions
Population balance model; Optimization; Breakage and Selection functions
How to refer
Patrícia Mundim Campos Faria;
Luís Marcelo Tavares;
Raj K. Rajamani.
POPULATION BALANCE MODEL APPROACH TO BALL MILL OPTIMIZATION IN IRON ORE GRINDING
,
p. 4930-4938.
In: 44º Seminário de Redução de Minério de Ferro e Matérias-primas, 15º Simpósio Brasileiro de Minério de Ferro e 2º Simpósio Brasileiro de Aglomeração de Minério de Ferro,
Belo Horizonte - Brasil,
2014.
ISSN: 2594-357X
, DOI 10.5151/2594-357X-25363
