Wear is an unavoidable but often underestimated factor in bulk material handling, leading to system inefficiency, component failure and costly downtime of material handling equipment. It causes structural damage, shortens equipment lifespan, extends maintenance times and reduces productivity. Wear is an inherently complex phenomenon in the world of granular materials, typically categorised as abrasive or impact, with various sub-mechanisms. Due to this complexity, numerous numerical wear models have been developed that differ in their predictive ability, computational efficiency and suitability for specific wear mechanisms and conditions. However, not all models accurately describe wear in highly dynamic granular systems. This study aims to implement and compare different numerical wear models by using Discrete Element Method (DEM) to simulate granular material flow, focusing on resolved and unresolved approaches. Widely used wear models, including Archard’s law and impact energy-based formulations, are compared to evaluate their ability to predict equipment wear. The models are implemented and tested in ANSYS Rocky to demonstrate their applicability in industrial wear prediction. The influence of key parameters such as particle shape, contact forces and material properties are systematically evaluated. In addition, this study aims to lay the groundwork for the future development of a new hybrid wear model that would enable more comprehensive wear prediction. The results of the benchmarking tests show significant differences in the predictions of different wear models. The simulation results are compared with experimental data and theoretical predictions available in the research literature to validate the numerical results. The study concludes that selecting an appropriate wear model requires careful consideration of the application-specific conditions, with a focus on balancing predictive accuracy and computational efficiency. These findings will be discussed in detail in the conference paper.