Simulation of Energy Consumption in Jaw Crusher Using artificial intelligence models

Abstract

Crushing is an important operation in a variety of industrial applications since it requires a significant amount of energy to blast materials into certain sizes of shattered boulders. Because accurate predictions of the energy required to manage this process are rare in the literature, there have been few efforts to reduce power consumption at the crushing stage by using a jaw crusher, which is the most common type of crusher. The availability of precise power predictions, as well as the optimization of initial crushing processes, would provide useful tools for selecting the best crusher for a given application. The Adaptive Neuro-Fuzzy Interference System is used to predict the particular power consumption of a jaw crusher in this study (ANFIS). Apart from the power required for rock comminution, the analysis includes an optimization of the crushing process to lower the projected power. In comparison to real data, the results show that the model is successful in correctly estimating comminution power with an accuracy of more than 96%. The findings provide valuable information that can be applied to future studies.