# Ginding Kinetics Adjustment of Copper Ore Ginding in an Innovative Electromagnetic Mill
## 1 Introduction
Mathematical modeling methods and modern simulation software allow examining various variants of technical implementation of the process with a high level of accuracy in order to determine the optimal model structure and parameters and find the possibilities of improving the process itself. In mineral processing, statistical methods are used to analyze the effects of experimental work, whose main objectives are to assess the resource's beneficiation and its improvement, as well as obtain information on the processes to determine the best results for a given beneficiation method [9]. Statistical methods are also used in the study of the mechanism of phenomena occurring in the processing to find the optimal process conditions. Through applying appropriate statistical methods, one can develop the results of either an active or a passive experiment. Process modeling allows designing and executing algorithms that are used in the electromagnetic mill control system. Such algorithms enable to control the real-time analysis of particle size distribution, the operating status of the mill, and recycle flow. With a layer of algorithms, properly designed measurement equipment defines the parameters of the final product quality and energy consumption. Models also allow the next step in the development program based on simulation studies, which involves assessing the industrial impact of the scaling of physical parameters on the individual parameters regarding quality and efficiency. In the processing of mineral raw materials, the modeling of phenomena and processes is particularly problematic due to the multitude of variables, the occurring interactions between them, and the variability of the parameters of the material being processed, between which the non-linear nature of connections often occurs [8]. The general parameters ensuring the specific final effects of the process can be divided into three basic groups: feed characteristics, device characteristics, and material distribution conditions. Therefore, there is no single-patterned modeling scheme, since the processing has various natures and runs according to different physical and physicochemical principles in different configurations (schemes) depending on the type of processed raw material [8]. In particular, these problems occur during the beneficiation of sulfide copper ores. The specificity of the feed and the way it is processed is not a simple task, and the models characterizing individual processes have been sought for years. Flotation is the main process of copper ore beneficiation. It requires fine particles with a size of 0.02-0.1 mm [10; 11; 12; 13]. Therefore, the selection of appropriate process parameters, such as grinding media characteristics and grinding time, is a key issue [10; 14]. At the same time, attention should be paid to too small particles deteriorating the quality of flotation concentrates. Polish copper ores are characterized by a complex structure and diversified mineralization, which translates into difficulties during beneficiation [15; 16]. The size of the copper-bearing minerals in the feed is estimated at 0.03-1.5 mm; therefore, it is important to obtain the appropriate characteristics of the grinding products that are loaded to the flotation nodes. In the paper [15], it has been shown that mineralization in some cases even forces the need to obtain feed with a particle size below 0.01 mm. However, the processing systems are based on the flotation of a material with 70-75% of 0-0.041 mm particle size fraction. In such a case, the optimization of the grinding is a key issue. The electromagnetic mill (EMM) is an innovative grinding device in which the rotating electromagnetic field is generated and then used for moving ferromagnetic grinding media in the working chamber. The innovative concept assumes a vertical position of the working chamber. Feed is delivered from the top, and the stream of transport air is delivered from the bottom.