Bauxite quality index (BQI) as a new criterion for the bauxite ore quality: A case study

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Article Type:
Case Study (دارای رتبه معتبر)
Abstract:

SummaryThe Module Index (MI = Al2O3/SiO2) is a criterion for determining the ore quality in bauxite deposits. Despite of wide use of the MI, it can not provide reliable criteria for determining of the ore quality due to less statistical attention to outlier data. In this paper, we have introduced the Bauxite Quality Index (BQI) as a new criterion for determining of the bauxite ore quality. We used geochemical data of the Jajarm bauxite deposit to evaluate the ability of the mentioned index. The BQI could be able to classify the ore zones based on the ore quality and economic importance. The BQI would be control the outlier data and reveal relationship between the variables, which are the most important characteristics of this index.IntroductionBauxite is the most important source of aluminum. The quality of bauxite ore depends on mineral composition of the ore which has been calculated by the Module index (Al2O3/SiO2 ). This paper introduced more comprehensive bauxite quality index (BQI) than the MI, using multivariate statistical analysis. We apply geochemical data of the Jajarm bauxite deposit to evaluate the ability of the BQI. Methodology and ApproachesThe BQI is determined based on factor analysis of geochemical data of the Jajarm bauxite deposit. We investigate the relationships between ore quality and alumina-silica contents using the MI and BQI. Then, the economic potential of the ore zones is evaluated by either MI and BQI. Finally, the correlation coefficients of the different parameters are calculated, and the all obtained results are compared and discussed. Results and ConclusionsThe Bauxite Quality Index (BQI) is a new suggested criterion for determination of bauxite ore quality. This criterion reveals hidden relationships of Al2O3 and SiO2 with other variables and outlier data. Comparison of the MI and the BQI indicates that the BQI is more reliable than the MI in recognition of the high grade ore bodies. x.

Language:
Persian
Published:
Journal of Aalytical and Numerical Methods in Mining Engineering, Volume:9 Issue: 21, 2020
Pages:
59 to 67
https://magiran.com/p2123701  
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