Simulation of Random Tagged Ore Flow through the Bunker in a Belt Conveying System

Abstract

Modelling the flow of a non-homogeneous ore is an important element needed to identify ore parameters for the purpose of ore processing control. The simulation model of the underground ore haulage system with the implemented function of estimating ore qualitative and quantitative parameters was built in the dedicated FlexSim simulation environment to address this issue. The transported ore is averaged in transfer and retention points, for instance in ore bunkers. This fact renders the modelling of ore flow inside the bunker a necessary part of the simulation. The movement of the granulated material, restricted by the geometry of the floor and walls, is modelled using Discrete Elements Method (DEM) with regard to the technological cycles of bunker filling and emptying. An experimental task was conducted on the site to identify the transport time of RFID tags that flowed together with the portions of ore they annotated. Empirical model of the transport system in the KGHM Lubin mine was parameterized with mean retention times obtained in DEM simulations in order to be compared with the RFID-tag experiment. The as-parameterized FlexSim simulation for one-chute bunker discharge variant yields tag transport times comparable with the experimental data. The results proved the reliable description of the ore transport time in the FlexSim model.

Copper Ore Quality Tracking in a Belt Conveyor System Using Simulation Tools

“…For the two-chute and one-chute bunker discharges, two values of mean retention time were incorporated into the FlexSim model-80 and 120 min, respectively. It was found that the one-chute bunker discharge variant of the FlexSim simulation complied well with the experimental time, while in the twochute variant the RFID tag flow times were shorter by about two hours (Bardzinski et al 2018). Within the experiment, some of the RFID tags were crushed or stuck to the mud and would therefore never reach the process plant.…”

“…Any significant deviation from the plans requires the simulation to be restarted for new operating parameters of the system. The model can also be used to make economic decisions about further exploitation of each mining field, because it shows the contributions of each ore source to the total production of the metal, which was presented in previous studies (Bardzinski et al 2018(Bardzinski et al , 2019.…”

“…In the current study, in order to represent the geological diversity of different mining fronts, lithological information was arbitrarily chosen and is shown in Table 3. The model can also track the variations in copper yield (Bardzinski et al 2018(Bardzinski et al , 2019), but the current study was limited to show changes in ore lithology.…”

“…Then, on Mondays, the bunker is almost empty. As the experiment was started on Monday, the first portions of the ore (as well as the RFID tags dropped first) were stuck in the bottom of the container, which explains their longer flow times (Bardzinski et al 2018).…”

“…Ore portions from different parts of the mine, with various lithologies, were marked with RFID tags with ascribed qualitative and quantitative information. The flow time of the tags between each loading point and the process plant was recorded (Kró l et al 2016;Jurdziak et al 2017b; Bardzinski et al 2018). FlexSim was chosen to build the model of the transport system of the underground copper mine in the current project, which was successfully tested by comparing the experimental RFID tag flow times.…”