Enhancement of Wear Resistance of High-Load Pressing Screw in Smokeless Charcoal Production by Using Genetic Algorithm and Discrete Element Method

During the production of smokeless charcoal, the pressing screw of the sawdust compressor is exposed to the effects of friction and elevated temperature, resulting in rapid wear. This phenomenon not only diminishes productivity but also exerts adverse influences on the final product's quality. Consequently, the pursuit of research endeavors aiming at prolonging the lifespan of the pressing screw holds significant importance, not only in reducing production costs but also in enhancing the product's overall quality. This paper adopts an innovative approach by integrating theoretical calculations, numerical simulations with practical experiments to ascertain the optimal profile for the pressing screw. This methodology employs Genetic Algorithm and Discrete Element Method (DEM) simulations in conjunction with the EDEM software to simulate the working process and provide the optimal profile of the pressing screw. The analysis and simulation results indicate a substantial enhancement in the wear resistance of the pressing screw while ensuring the efficient movement of discrete materials during the pressing process. The results of this study not only indicate the main wear locations on the pressing screw but also suggest the optimal profile, providing a basis and control for wear assessment. Furthermore, the results of this research not only identifies the principal areas that are susceptible to wear on the pressing screw but also proposes optimal profile, threreby establish a solid foundation and methodology for wear assessment. These results will be pragmatically implemented in smokeless charcoal production factories, concurrently pave the way for further research and applications in this field.