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Investigation effect of copper particle size and jaw geometric configurations on jaw crusher wear
 
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Universidad Nacional de San Agustín de Arequipa, Arequipa 04000, Peru
 
These authors had equal contribution to this work
 
 
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Christofer Alex Diaz Arapa   

Universidad Nacional de San Agustín de Arequipa, Arequipa 04000, Peru
 
 
 
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ABSTRACT
The growing demand for efficiency in industrial crushing processes has highlighted the need to understand particle behaviour in jaw crushers in order to minimise wear and maximise productivity. In response, analysing the influence of particle size and jaw geometry can play a crucial role in reducing operating costs and increasing equipment life. This study explores the relationship between different material sizes and the geometric configurations of movable and fixed jaws in the wear of jaw crushers. A comparative analysis was performed using simulation to evaluate wear through a discrete element method-multibody dynamics-particle replacement method (DEM-MBD-PRM) coupling with the Tavares fracture model and the Archard wear model. Prior to simulation, material and contact parameters were calibrated in EDEM software to ensure reliable representation of copper–steel interactions. This analysis process led to a better understanding of tribological behaviour. Configurations with smaller particle sizes, in the range of 80 to 100 mm, reduced wear by up to 50% compared with larger particles, in the range of 100 to 120 mm, with distinct wear patterns observed between sharp and standard profiles. Additionally, simulation showed that jaws with sharp profiles typically had longer service lives, suggesting that the configurations with standard profiles and large particle sizes are the most susceptible to wear. The findings of this study demonstrate that optimising feed particle size and jaw geometry can reduce wear on crusher components by up to 50%, directly contributing to more efficient crushing operations, extended equipment lifetime, and lower maintenance costs. Although the study was uniquely based on computational modelling without an experimental verification, the results provide a solid framework for the guidance of future physical testing and design improvements.
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