University of TehranInternational Journal of Mining and Geo-Engineering2345-693056420221201Model development for prediction of autogenous mill power consumption in Sangan iron ore processing plant3013078630710.22059/ijmge.2022.320882.594899ENDavoodNamaei RoudiFaculty of Engineering, University of Birjand, Birjand, IranAliBehnamfardFaculty of Engineering, University of Birjand, Birjand, Iran0000-0002-9024-1881Journal Article20210318The variables including ore hardness based on the SAG power index (SPI), particle size of mill product (P80), trunnion pressure of the mill free head (p) and working time period of mill liner (H) were considered as variables for development of an adequate model for the prediction of autogenous (AG) mill power consumption in Sangan iron ore processing plant. The one-parameter models (SPI as variable) showed no adequate precision for the prediction of Sangan AG mill power consumption. Two-parameter models (SPI and P80 as variables), proposed by Starkey and Dobby, showed no adequate precision for the Sangan AG mill power consumption. Nonetheless, by exerting an adjustment factor in the model (0.604513 which obtained by what-if analysis using Solver Add-Ins program), the model precision increased significantly (an error of 7.11%). Finally, a four-parameter model in which the Sangan AG mill power consumption is predicated as a function of SPI, P80, p, and H was developed. Hence, initially the relationship between the mill power consumption and each of the variables was obtained and then the four-parameter model was developed by summation of these four equations and applying a similar coefficient of 0.25 for all of them. This model was modified through finding the best coefficients by what-if analysis using solver Add-Ins program through minimizing the ARE error function. The error function for the training and testing data sets was determined to be 2.93% and 2.39%, respectively.https://ijmge.ut.ac.ir/article_86307_30c2955e9885a293fbfd550fd40b0ef4.pdf